ORMS Today - June 2017

LINEAR PROGRAMMING SOFTWARE SURVEY

June 2017

Volume 44 • Number 3 ormstoday.informs.org

The future of scientific funding

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Contents June 2017 | Volume 44, No. 3 | ormstoday.informs.org

20 On the Cover Is Science Under Siege?

Funding for science and research is under fire under the new administration. What will the future bring, and how should INFORMS members respond?

Image © Angela Waye | 123rf.com

F e at ure s 20

Holiday Retirement receives Edelman

24

Models that are never wrong

28

Enterprise optimization: new application

34

ORSI turns 60

By Peter Horner Senior living firm wins “Super Bowl of O.R.” thanks to revenue management, unique application, benefit to residents.

By Ignacy Kaliszewski and Douglas A. Samuelson MCDM essentials: New toolkit for multi-criteria decision-making returns control to the decision-maker.

de partm e nt s

6 8 10 12 14 16 18 19 60 61 64

Inside Story President’s Desk Forum Issues in Education INFORMS in the News INFORMS Initiatives PuzzlOR Viewpoint Industry News Classifieds ORacle

By Alan Dybvig and Gary Cokins The demand-driven operational income statement integrates prescriptive optimization and predictive analytics.

2 | ORMS Today

By Krishnendranath Mitra and Goutam Dutta History of O.R.: Operational Research Society of India prepares to celebrate multiple milestones this year. |

June 2017

34 ormstoday.informs.org

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June 2017 | Volume 44, No. 3 | ormstoday.informs.org

48

INFORMS Board of Directors

President Brian Denton, University of Michigan

President-Elect Nicholas Hall, Ohio State University

Past President Edward H. Kaplan, Yale University

Secretary Pinar Keskinocak, Georgia Tech

Treasurer Michael Fu, University of Maryland

Vice President-Meetings Ronald G. Askin, Arizona State University Vice President-Publications Jonathan F. Bard, University of Texas at Austin

Co m puting 48

Vice President- Russell Barton, Sections and Societies Pennsylvania State University

Vice President- Marco Luebbecke, Information Technology RWTH Aachen University

Software Survey: Linear Programming

By Robert Fourer Fourteenth in a series of LP surveys focuses on characteristics that are valuable in choosing products.

Vice President- Jonathan Owen, CAP, General Motors Practice Activities Vice President- Grace Lin, Asia University International Activities

Vice President-Membership Susan E. Martonosi,

Professional Recognition Harvey Mudd College

Vice President-Education Jill Hardin Wilson, Northwestern University Vice President-Marketing, Laura Albert, Communications and Outreach University of Wisconsin-Madison Vice President-Chapters/Fora Michael Johnson, University of Massachusetts, Boston

Editors of Other INFORMS Publications

39

Decision Analysis Rakesh K. Sarin, University of California, Los Angeles

Editor’s Cut Anne G. Robinson, Verizon

Information Systems Research Alok Gupta, University of Minnesota I NFORMS Journal on Computing David Woodruff, University of California, Davis

INFORMS Transactions Jeroen Belien, KU Leuven on Education

Interfaces Michael F. Gorman, University of Dayton

Management Science Teck-Hua Ho, National University of Singapore

news

Manufacturing & Service Christopher S. Tang, Operations Management University of California, Los Angeles

Marketing Science K. Sudhir, Yale University

Mathematics of Operations J. G. “Jim” Dai, Cornell University Research

Operations Research Stefanos Zenios, Stanford University

Organization Science Gautam Ahuja, University of Michigan

Service Science Paul P. Maglio, University of California, Merced

Strategy Science Daniel A. Levinthal, Wharton School, University of Pennsylvania

Transportation Science Martin Savelsbergh, Georgia Institute of Technology

39 39 40 41 42 42

Preview: Annual Meeting Winter Simulation Conference Spring Roundtable Roundup Preview: Healthcare Conference USAF garners UPS Prize Student Team Competition

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43 44 46 47 47

Turner Broadcasting wins IAAA Photos: Scenes from Las Vegas Wagner Prize Recipients People Meetings

Tutorials in Operations J. Cole Smith, Clemson University Research

INFORMS Office • Phone: 1-800-4INFORMS

Executive Director Melissa Moore

Headquarters

INFORMS (Maryland) 5521 Research Park Dr., Suite 200 Catonsville, MD 21228 USA Tel.: 443.757.3500 Fax: 443.757.3515 E-mail: informs@informs.org

ormstoday.informs.org

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Inside Story

Peter Horner, editor

peter.horner@mail.informs.org

OR/MS Today Advertising and Editorial Office

Strange days, weird science

Send all advertising submissions for OR/MS Today to: Lionheart Publishing Inc. 1635 Old​41 Hwy, Suite 112-361, Kennesaw, GA 30152​USA Tel.: 888.303.5639 • Fax: 770.432.6969

President John Llewellyn, ext. 209 john.llewellyn@mail.informs.org

Editor

Readers of a certain age with a certain nerd quotient might recall the 1985 film “Weird Science” about a couple of teenage boys who “design their ideal woman on a computer, and a freak electrical accident brings her to life in the form of lovely, superhuman Lisa” (played by 1980s heartthrob Kelly LeBrock).

Yeah, I know, dumb concept, but hey, it’s Hollywood. The film made a lot of money, and that’s all that matters.

For some weird reason, that 32-yearold sophomoric film keeps crossing my mind during these strange days since the 2016 presidential election. Anyone who pays any attention to the news – real or fake, it doesn’t matter – knows that when it comes to science, such as the environment, climate change and what’s causing it, there’s something weird going on. The question is, who’s science are you going to believe? For example, is global warming a “hoax,” something “created by and for the Chinese in order to make U.S. manufacturing non-competitive,” or is it a natural phenomenon accelerated by man-made CO2 emissions?

I think we can all ag ree that “alternative facts” have no place in basic science and make no sense in the natural world. E = mc2 holds true throughout time and space. Yet the scientific community, known for the “scientific method” and its painstaking efforts to get to the truth of how the natural world works through “systematic observation, measurement and experiment, and the formulation, testing and modification of hypothesis” (Oxford Dictionary), is under siege from certain people in high places. Politics, of course, play a role, but one could also make the case that some research is unnecessary and not particularly useful or applicable, and 6 | ORMS Today

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when that research receives funding from the federal government, budgeting issues ensue.

And so it begins. According to ScienceNews, the administration’s proposed fiscal 2018 budget calls for significant cuts to the following agencies: National Science Foundation (11 percent cut), Environmental Protection Agency’s Office of Science & Technology (37 percent), Department of Energy’s Office of Science (16 percent), U.S. Centers for Disease Control and Prevention (17 percent) and the National Institutes of Health (22 percent). And that’s just the tip of the melting iceberg.

It’s important to remember that the president’s proposed 2018 budget is not the final budget, and many changes will no doubt be made between now and then. It’s also true that many dedicated researchers and scientists are doing great work that benefits society in countless ways, from healthcare, manufacturing and defense to energy and transportation.

In this issue’s “President’s Desk” column, Brian Denton describes proposed cuts to scientific funding as an important “wake-up call” for the operations research/ analytics community, noting that, “there is a longstanding history of challenges in making the connection between basic science and societal impact.” Denton urges INFORMS members to respond to the challenge by taking action in a constructive manner. For more, see page 8. Meanwhile, in a related “Forum” piece, Laura Albert, INFORMS Vice President of Marketing, Communications and Outreach, outlines opportunities for O.R. at the National Science Foundation (page 10).

Trust me, there’s nothing strange or weird about either of their articles. Just the (real) facts. ORMS

Peter R. Horner peter.horner@mail.informs.org Tel.: 770.587.3172

Assistant Editor Donna Brooks

Contributing writers/editors Douglas Samuelson, John Toczek

Art Director Alan Brubaker, ext. 218 alan.brubaker@mail.informs.org

Online Projects Manager Patton McGinley, ext. 214 patton.mcginley@mail.informs.org

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Advertising Sales Managers Sharon Baker sharon.baker@mail.informs.org Tel.: 813-852-9942

Reprints Kelly Millwood, ext. 215 kelly.millwood@mail.informs.org

OR/MS Today Committee James Cochran, chairman

INFORMS Online http://www.informs.org

Lionheart Publishing Online http://www.orms-today.org OR/MS Today (ISSN 1085-1038) is published bimonthly by the Institute for Operations Research and the Management Sciences (INFORMS). Canada Post International Publications Mail (Canadian Distribution) Sales Agreement No. 1220047.

Deadlines for contributions: Manuscripts and news items should arrive no later than six weeks prior to the first day of the month of publication. Address correspondence to: Editor, OR/MS Today, 1635 Old​ 41 Hwy, Suite 112-361, Kennesaw, GA 30152​. The opinions expressed in OR/MS Today are those of the authors, and do not necessarily reflect the opinions of INFORMS, its officers, Lionheart Publishing Inc. or the editorial staff of OR/MS Today. Membership subscriptions for OR/MS Today are included in annual dues. INFORMS offers non-member subscriptions to institutions, the rate is $62 USA, $79 Canada & Mexico and $85 all other countries. Single copies can be purchased for $10.50 plus postage. Periodicals postage paid at Catonsville, MD, and additional mailing offices. Printed in the United States of America. POSTMASTER: Send address changes to OR/MS Today, INFORMS-Maryland Office, 5521 Research Park Dr., Suite 200, Catonsville, MD 21228. OR/MS Today copyright ©2017 by the Institute for Operations Research and the Management Sciences.

All rights reserved.

ormstoday.informs.org

What’s Your StORy?

Ranganath S. Nuggehalli, CAP Principal Scientist, UPS INFORMS member since 1987 What prompted you to enter this field? Why? Growing up in a farming family in a Third World country, you are naturally indoctrinated to conserve and be efficient. I always used to think about how to make things better/last longer. While doing my MBA at Texas Christian University, I was introduced to the field of operations research, and I was naturally attracted to it.

What has been your favorite INFORMS experience so far?

It is difficult to single out one, for there are many.

However, being part of the team that made the UPS George D. Smith Prize a reality does rank high. It was a great team of people from the INFORMS Practice Section that worked with INFORMS and UPS and made the prize happen. It is gratifying whenever I hear from an applicant how competing for the prize has brought fresh perspective about their program.

Tell us about your experiences with the Edelman competition – from being a finalist to a winner, and then a coach.

It is a unique, humbling, and gratifying experience. It was a great group of finalists, and anyone could have been the winner. The project was very well known within UPS with proven benefits. It was gratifying that our CEO David Abney volunteered to be a presenter and made time to come to the Analytics Conference in Orlando last year even though he had a hectic schedule and had to fly back late in the night. My experience as a finalist also helped me to be a better coach.

If you had to work on only one project for the next year, what would it be?

Two years ago I participated in a scenario planning workshop that was held at West Point. The goal was to plan a defense scenario for 2050. Since then my interest in this field has increased.

In a way this is the opposite of what we, the O.R. professionals do. I would love to do a scenario plan for UPS in either 2030 or 2040.

More questions for Ranganath?

!" #$%&'(!)*&!+%& ,&-!)./0/-!.(1&/2&!&*0(2!)/%&-3!22/2+&$%)4*5%-&.5!.&$!*&5(31&!.& 6 (*.& Ask him in the Open Forum on INFORMS Connect!

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http://connect.informs.org

President’s Desk

Brian Denton

INFORMS President president@informs.org

Return on investment from (operations) research A large portion of our membership is engaged in research at universities, in industry and government labs. As a result, it is no surprise that many of us are deeply concerned about recent proposed changes that threaten progress in research. I believe these concerns stem from a common theme: the difficulty in connecting research to economic and societal impact. In this article, I summarize concerns about recent events, and I give some specific examples of the impact of research. My choice of this topic is based on recent events in the United States, but the central issue of return on investment from research is important to all members who engage in research.

A topic of great discussion over the last couple of months has been the proposed reductions in research funding to U.S. government agencies. Many of our members rely on these agencies, such as the National Science Foundation (NSF) and the National Institutes of Health (NIH), as a source of faculty salary, funding for graduate student research assistants and postdoctoral fellows. This funding makes it possible to educate and mentor the next generation of professors and industry research staff members. So, it is natural that many people are deeply concerned about what these reductions could mean for progress in our field. (For more on NSF funding opportunities, see Laura Albert’s “Forum” article on page 10).

First, some good news. Last month I had the opportunity to attend a budget briefing on Capitol Hill organized by the American Association of Engineering Societies. The analysis included a review of the proposed “skinny budget” that calls for dramatic cuts to government research funding in the United States.The briefing took an hour, but the final summary was simple.

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Major cuts in funding to NSF, NIH and the Department of Defense are unlikely (although some sources such as the Department of Energy and the Environmental Protection Agency are at risk). As of this writing, we have seen approval of a budget through fall 2017 that is flat for NSF (good news, all things considered) and includes a $2 billion increase for NIH. In spite of the relief over averting major cuts this year, this is an important “wake up” call for our field. There is a longstanding history of challenges in making the connection between basic science and societal impact. The reasons for this include the long lead times for the translation of research to practice and the high risk associated with basic research, particularly theoretical or methodologically focused research. In fact, these challenges are what drive the need for government funding, because high-risk research with long payoff times is often not viable in an industry context where shareholders focus on quarterly returns. Nevertheless, making the case for economic and societal impact from research is necessary to justify public funding.

Research into new methods and theoretical advances in our field (e.g., optimization, stochastic models and simulation) are often the hardest to justify from a societal perspective. However, the collective knowledge derived from these research areas has led to extraordinary advances. For example, without the field of optimization we would not have the commercial packages that enable a robust power grid, operation of global supply chains or the design of radiation treatment plans for cancer patients. Stochastic models and simulation are pervasive in many industries such as healthcare where they are routinely used to analyze medical

treatment decisions and climate science where they predict and plan for natural disasters. Industry-leading organizations such as Amazon, General Motors, Google, IBM, Mayo Clinic and SAS, to name a few, leverage these advances to drive innovation and competitive advantage. The INFORMS journal Interfaces is a great resource for success stories, but it communicates to our members and not to the broader public.

One of the most important outcomes from research is the professional development of the team members who conduct it. In our field, the majority of government research dollars go to students and postdoctoral fellows. This is part of our culture – education through research – and its importance should not be underestimated. Dramatic cuts in government research funding would cause an immediate reduction in opportunities for graduate students and postdoctoral fellows.

This comes while we are experiencing high demand from industry and academic institutions for people with advanced degrees in our field.

Basic research in our field has improved the world with managerial insights and advanced methods that are available in software packages that are routinely used to achieve economic gains, improve human health, and increase safety and national security. Cuts to research would jeopardize our field’s ability to respond to the next generation of societal problems, but without making the case to the public, this may be inevitable. Therefore, I encourage you to engage in public dialogue with people outside our field.Write a press release, contact your congressman, create a YouTube video, write an article aimed at the general public or visit a local high school to talk to students about our field. Better yet, come up with new innovative ideas to get the word out about the impact of what we do. ORMS ormstoday.informs.org

Healthcare 2017 OPTIMIZING OPERATIONS & OUTCOMES INFORMS Healthcare 2017 brings together academic researchers in “healthcare analytics” and industry stakeholders who are applying and sharing research to improve the delivery of effective healthcare.

NETWORK WITH MEMBERS

JOIN US IN ROTTERDAM, JULY 26–28 The conference offers the healthcare community a platform to take the next step on the path to optimizing health and advancing the theory and practice of operations research and analytics. Technical sessions will cover areas such as disease & treatment modeling, personalized medicine, medical decision making, healthcare analytics & machine learning, health IT & management, health operations management, health & humanitarian systems, disparities in health & global health, and public health & policy making.

LEARN BEST PRACTICES

Keynote Speakers Dimitris Bertsimas

Operations Research Center Massachusetts Institute of Technology

Brian Denton

Department of Industrial and Operations Engineering University of Michigan

Dr. Eric de Roodenbeke

CEO, International Hospital Federation

Margaret Brandeau

Stanford University Philip McCord Morse Lecture: "Public Health Preparedness: Answering (Largely Unanswerable) Questions with Operations Research"

REGISTER TODAY http://meetings.informs.org/healthcare2017

HEALTHCARE 20 7

TAKE SOMETHING BACK

Forum

By Laura Albert

Opportunities for O.R. at the National Science Foundation The mission of the National Science Foundation (NSF) is to “promote the progress of science, to advance the national health, prosperity and welfare; to secure the national defense.” To support this mission, NSF supports fundamental research and education.

Georg ia-Ann Klutke and Ir ina Dolinskaya are the program directors for the new Operations Engineering (OE) program, the main program at NSF that supports research in operations research.

I recently attended one of GeorgiaAnn Klutke’s presentations about the OE program and talked with her about opportunities for O.R. at NSF. The OE program replaced the Service, Manufacturing and Operation Research (SMOR) program in February 2017, as announced in a “Dear Colleague Letter.” According to Klutke, the goal of the OE program is to improve operations decisions to support

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real systems. The OE program focuses on research proposals that have huge potential impact on the operational aspects of important engineering applications and should enable improved decision-making capabilities. Collaborative research is valued in proposals to the new OE program, and Klutke recommended collaborations with those who have different, non-overlapping skill sets.

The long-term strategy for the OE program is to broaden participation and enhance diver sity in the OE portfolio. Klutke mentioned a few emerging application areas in datadriven environments that could benefit from operations research, including healthcare delivery that occurs outside the walls of a hospital, manufacturing operations, supply chains in human trafficking and adversarial networks, and public safety. She is supportive of funding workshops in emerging application areas that would be attended by domain experts as well as researchers. The funding windows for unsolicited proposals have changed to Sept. 1-15 and Jan. 10-24 each year. The SMOR prog ram offered a common level of support for each proposal, and the OE program plans to fund small, exploratory awards as well as medium and large awards to give investigators what they need to do the research.

Oppor tunities for operations research outside o f t h e O E p rog r a m

in cross-cutting programs and special solicitations include: • Smart and connected health, • computational and data-enabled science and engineering, • cyber-physical systems, and • critical resilient interdependent infrastructure systems and processes.

The dear colleague letter announced a controversial change to what the program will not fund: “The OE program is highly supportive of leveraging funds across NSF programs but is not the primary source of funding for purely methodological or algorithmic research.”

Klutke confir med that purely methodological research will not be funded by the new OE program. She explained that the OE program is clearly carving out its niche, and other programs will fund the methodological or algorithmic research niche. For methodology, she recommended programs in algorithmic foundations (in Computer & Information Science & Engineering (CISE)) and applied mathematics (in Division of Mathematical Sciences (DMS)), compu tational mathematics (in DMS), probability (in DMS) and statistics (in DMS). She recommended that researchers in these areas volunteer to serve on review panels so that operations research becomes valued in these programs.

Klutke and Dolinskaya are working to co-fund O.R. proposals in different programs. Some of these programs include Civil Infrastructure Systems; Manufacturing Machines and Equipment; Energy, Power, Control and Networks; I n f r a s t r u c t u re M a n a g e m e n t a n d Extreme Events; and Decision, Risk and Management Science. ORMS Laura Albert is the assistant dean for Graduate Studies in the College of Engineering and an associate professor in Industrial and Systems Engineering at the University of Wisconsin-Madison. She is also the INFORMS vice president of Marketing, Communication and Outreach.

EDITOR’S NOTE: For more on federal funding of O.R.-related research, see INFORMS President Brian Denton’s “President’s Desk” column on page 8.

ormstoday.informs.org

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Issues in Education

By Irv Lustig

Survey: Analytics student population continues to grow The population of students studying analytics is increasing, according to an informal Princeton Consultants snapshot survey at the INFORMS Annual Meeting last November in Nashville, Tenn. Most students’ future plans are academic or research-oriented; for those who intend to become practitioners, consulting is the leading industry choice.

The non-scientific study involved 111 self-selected survey participants, all of whom were onsite at the conference.

The participants included 73 students, 33 professors and five practitioners.

Princeton Consultants reported the following findings: • 23.6 percent of students said they intend to become analytics practitioners at for-profit or nonprofit organizations; the remainder plan to remain in academia or perform research.

• For students intending to work at a for-profit business, consulting is the most preferred of 14 industries, followed by financial services and healthcare.

• 94 percent of professors said the student population in analytics at their schools has increased or remained the same size during the last three years.

• Professors who belong to INFORMS teach analytics in a variety of departments and schools, led by Business Administration (MBA) and the Operations Research Department.

Figure 1

Figure 2

Participating professors answered the following: In the past three years at my institution, the size of the student population that is studying OR/Analytics has: See Figure 1.

I teach in the following department/ school: See Figure 2.

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Figure 3 ormstoday.informs.org

Participating students answered the following: After graduation, my first preference is to: See Figure 3.

Students who had selected working as a practitioner at a for-profit organization answered the following: I would consider enter ing the workforce as a practitioner for a for-profit organization in the following industries (check all that apply): See Figure 4.

Figure 4

Students who had selected working as a practitioner at a non-profit organization answered the following: I plan to enter the workforce as a practitioner at a governmental or nonprofit agency in the following area: See Figure 5. ORMS Irv Lustig is an optimization principal at Princeton Consultants (www.princeton.com/ advancedanalytics) and a longtime, active member of INFORMS.

Figure 5

June 2017

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INFORMS in the News

Compiled by Ashley Kilgore

Edelman, marketing, online reviews and more Prorize earns top analytics award for work with Holiday Retirement Pror ize, a provider of revenue management solutions, announced that they and their customer, Holiday Retirement, the largest private owner and operator of independent senior living communities in the United States, was jointly awarded the Franz Edelman Award.The award, sponsored

by INFORMS, recognizes and rewards outstanding contributions of analytics and operations research in for-profit and nonprofit sectors around the globe.

- KLTV 7-ABC, May 5

Why paying users to write reviews of products is probably a bad idea It’s a bit of an understatement to say that consumers have come to rely on the internet.

For everything from work to entertainment, there’s an online aspect that usually makes things easier or more convenient. This is especially true when it comes to shopping.

Online sites like Yelp, ConsumerAffairs and TripAdvisor, and forums such as those found on Amazon and even Reddit, have made making an informed purchase that much easier. So, should these sites pay consumers for their review insights? While your curiosity might be piqued at the idea of being paid to share your opinion, a study in the INFORMS journal Marketing Science showed that paying users to encourage them to write reviews is probably a bad idea.

- Consumer Affairs, May 2

University of Montana students head to Vegas for business analytics University of Montana (UM) students Brandon Staggs and David Brewer spent a week in Las Vegas, where they, err, did a lot of homework. Staggs and Brewer graduate this year as part of the first Master’s of Science in Business Analytics cohort at UM. They were also part of the first UM team to attend the INFORMS Business Analytics conference inVegas, where they interviewed with companies such as Amazon, GM Financial, Deloitte and MGM Grand.

- Missoulian, April 24

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Air Force, Walt Disney Co. receive operations research award Members of the Air Force Studies, Analysis and Assessments directorate joined leaders of the Walt Disney Company as coawardees of the INFORMS Prize at a gala in Las Vegas on April 3 for their pioneering and enduring integration of operations research and analytics programs.The award is given each year by INFORMS.

a part-time offering through York’s School of Continuing Studies, the big data analytics program is comprised of two certificates – the certificate in big data analytics and the certificate in advanced data science and predictive analytics. The certificate in advanced data science and predictive analytics, which launches in winter 2018, delves into data organization for analysis and advanced methods and analytics for those looking to pursue the INFORMS Certified Analytics Professional (CAP®) designation, the premier global professional certification for analytics practitioners.

- Aerotech News, April 21

- The Toronto Star, April 12

The complexity of ‘cause marketing’ campaigns Cause marketing, or marketing campaigns involving the combined efforts of a for-profit and non-profit organization, is commonly conducted in retail shops, restaurants, movie theaters and even online.

Whether you are attending a “give back” night at Chipotle or a special charity event at a local boutique, cause marketing campaigns seem like the perfect situation for all parties involved. However, a new study in the INFORMS journal of Marketing Science found that the effects of cause marketing are more complicated than that.

The most impactful technologies coming to retail Suresh Acharya, INFORMS member and head of JDA Labs, discussed how, thanks to a shift in focus from “stuff ” to “people,” data science and machine learning are poised to take retail to new levels of efficiency, profitability and customer satisfaction.

- USAgNet.com, April 21

From roadways to telecommunications, where should America invest in its networks?

As the current White House administration prepares to invest hundreds of billions in its infrastructure networks, Anna Nagurney, INFORMS Fellow and professor at the University of Massachusetts at Amherst, shared how operations research can help identify where those investments will have the most impact.

- The Conversation, April 19

Become a part of the growing data analytics field Researchers have estimated that 150,000 data analytics professionals are needed to fill roles in Canada.York University announced it will help to address the talent shortage by launching its big data analytics program this September. Facilitated as

- Retail Touch Points, April 11

Can tailoring ads help brands increase customer loyalty?

Maarten Bos, a research scientist at Disney Research, helped conduct a series of studies – which were the topic of his presentation at the 2017 INFORMS Business Analytics Conference – about tailoring ads that are both appealing and effective. Personality types vary, which suggests that tailored advertisements may be appealing and effective.

- Loyalty 360, April 11

How Holiday increased revenue from new leases by 10 percent What started around 2011 as an effort to find a better way to establish appropriate unit rents led Lake Oswego, Ore.based Holiday Retirement to consistently realize a 10 percent revenue increase from new leases. In recognition of this achievement, Holiday Retirement received an international award, the INFORMS Franz Edelman Award, for implementing a revenue management system that was new to the senior living industry. ORMS - McKnight’s Senior Living, April 4 For links to all of the articles mentioned above, visit: http://bit.ly/2sExZBM

ormstoday.informs.org

ASSOCIATE CERTIFIED ANALYTICS PROFESSIONAL Analyze How aCAP Can Help Launch Your Analytics Career

The Associate Certified Analytics Professional (aCAP) is an entry-level analytics professional who is educated in the analytics process but may not have practice experience.

This prestigious program begins a career pathway leading to the CAP designation.

www.certiďŹ edanalytics.org

INFORMS Initiatives

Innovative apps, video library, skills workshop 2018 IAAA competition accepting entries Entries are now being accepted for the 2018 Innovative Applications in Analytics Award (IAAA) competition, sponsored by Cater pillar and the Analytics Society of INFORMS. The IAAA provides a forum for enterprising teams and organizations to receive recognition for applications that combine different types of analytics – descriptive, predictive and prescriptive – in creative and unique ways to achieve real-world impact.The award committee is finalizing an opportunity for this year’s best submissions to be published in a special issue of a flagship INFORMS journal.

Apply now and receive the credit you deserve for your innovative analytics application. For more information, contact IAAA committee chair Dr. Juan Jaramillo at jaramijr@farmingdale.edu.

INFORMS Video Library showcases 2017 award finalists Participants in the 2017 INFORMS Business Analytics Conference in Las Vegas in April had the opportunity to experience real-world case studies of a full spectrum of analytics in action, including the finalists for many of the INFORMSsponsored awards. For those who missed the award presentations, videos of this year’s award finalists are now available at the INFORMS Video Library (https:// www.informs.org/Resource-Center/ Video-Library).

The 2017 Franz Edelman Award finalists embraced analytics to enhance processes, save money and improve lives in a variety of applications from healthcare to mining operations.

Holiday Retirement, winner of the 2017 Franz Edelman Award, leveraged an advanced revenue management algorithm to completely revolutionize the pricing 16 | ORMS Today

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June 2017

model for its more than 300 senior living communities across the country. For more on this year’s Edelman competition and Holiday Retirement’s award-winning work, see page 20.

Other finalists included: • American Red Cross developed a new collection model that increased the amount of donated blood that can be collected and processed.

• High-tech screen production company Barco used product development platforms to reduce costs and improve its portfolio.

• As it expanded its mining portfolio, BHP Billiton used a new model to realize millions in additional project value.

• General Electric partnered with Norfolk Southern Railroad to implement a novel movementplanning algorithm to dispatch trains over a large rail network.

• The New York City Department of Transportation created a new off-hour deliveries schedule for businesses in the city that improves safety and sustainability.

The Innovative Applications in Analytics Award (IAAA) finalists for 2017 used analytics to create novel solutions that were applied to unique, new areas.

The winner of the 2017 award, Turner Broadcasting System, Inc., developed new models to provide targeted ad content to viewers.

Other finalists: Construction machinery manufacturer Caterpillar Inc. combined a supply network model with past and present data on dealers, customers and suppliers in order to increase situational awareness of any emerging issues and improve profits. The London School of Economics explored how to revitalize abandoned railway lines

and accompanying buildings, applying its findings to recently abandoned railway lines in Northern Italy.

The winner of the 2017 UPS George D. Smith Prize, the U.S. Air Force Academy, was recognized for the unique and exciting opportunities its students have to interact with industry representatives in preparation to become frontline O.R. practitioners as analysts in the Air Force.

Workshop aims to improve your essential soft skills In Inc. Magazine, Lou Adler wrote that, “People don’t underperform because they lack technical skills. People underperform because they lack soft skills.” Corporations and institutes of higher education tend to focus on teaching, assessing and maintaining technical skills, which are vital. Are “soft skills” any less important?

The Essential Practice Skills for HighImpact Analytics Projects workshop, part of the INFORMS Continuing Education program, is specifically designed to improve “soft skills” for analytics practitioners.

INFORMS will hold its most popular continuing education workshop in Atlanta on June 20-21 at Emory University’s Goizueta Business School.

The two-day, hands-on course was developed by INFORMS and facilitated

by Dr. Patrick Noonan, former assistant dean and director of MBA programs at the Goizueta Business School.

The course will also be offered in September in Washington, D.C., and in October in Houston.

For more information, contact Bill Griffin (bill.griffin@informs.org).

Pro Bono Analytics program accepting volunteers Make a difference in underserved communities by volunteering your time and talents to the INFORMS Pro Bono Analytics program.Volunteer opportunities are constantly being added. To learn more, visit: http://connect.infor ms.org/ probonoanalytics/home. ORMS ormstoday.informs.org

Connecting with the right audience isnâ&#x20AC;&#x2122;t rocket science.

Exhibit & SPonsor at the worldâ&#x20AC;&#x2122;s largest Operations Research & Analytics Conference For additional details, contact Olivia Schmitz at Olivia.Schmitz@informs.org or visit:

http://meetings.informs.org/houston2017 Houston, Texas

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October 22-25, 2017

PuzzlOR

John Toczek

puzzlor@gmail.com

A long walk Walking in large cities poses some risk to pedestrians. There are poorly designed intersections, mistimed lights and commuters in cars that are anxious to get to their destination.

My new commute to work includes a one-mile walk, which is represented in the accompanying map. Each line represents a segment of that walk, and the line color represents the level of risk for that segment. Red indicates a high risk section, orange indicates a medium risk section, and green represents a low risk section.

Move from circle to circle in any direction you like from start to finish while trying to minimize the total risk. To calculate the total risk of the walk, add up points for all segments as follows: green = 0 points, orange = 1 point, red = 2 points.

Question: What are the minimum total risk points that can be achieved for the walk?

Send your answer to puzzlor@gmail.com by Aug. 15. The winner, chosen randomly from correct answers, will receive a $25 Amazon Gift Card. Past questions and answers can be found at puzzlor.com. ORMS John Toczek is the senior manager of analytics at NRG in Philadelphia.

He earned his BSc. in Chemical Engineering at Drexel University (1996) and his MSc. In operations research from Virginia Commonwealth University (2005).

Danger ahead: A one-mile walking commute.

Prizes & Awards Deadlines

Each year INFORMS grants several prestigious institute-wide prizes and awards for meritorious achievement.

These prizes and awards celebrate wide ranging categories of achievement from teaching, writing, and practice to distinguished service to the institute and the profession and contributions to the welfare of society.

Case and Teaching Materials Competition Submission: August 26

Judith Liebman Award Nominations: August 25

Frederick W. Lanchester Prize Submission: June 15

Moving Spirit Award for Chapters Nominations: August 25

George B. Dantzig Dissertation Award Submission: June 30

Moving Spirit Award for Fora Nominations: August 25

George E. Kimball Medal Submission: July 31

Prize for the Teaching of the OR/MS Practice Nominations: June 30

George Nicholson Student Paper Competition Submission: June 15

Saul Gass Expository Writing Award Submission: July 1

INFORMS O.R. & Analytics Student Team Competition Register: September 30

Undergraduate Operations Research Prize Submission: June 15

John von Neumann Theory Prize Nominations: July 1

Volunteer Service Award Submission: June 30

https://www.informs.org/Recognizing-Excellence/INFORMS-Prizes

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ormstoday.informs.org

Viewpoint

By Carol Ozemhoya

Can technology create a risk-free market?

Some people worry about technology costing people jobs and taking over the world as has been portrayed in many major motion pictures, such as the “Matrix” series.

In fact, many of the advances in technology have made our lives easier and safer and, well, cheaper. Consider the cost of color TVs when they first came out and what they cost now … a mere fraction of the earlier models.

And the same goes for other electronics, including computers and smart phones, and those very same electronic devices are processing information faster than ever.

There’s also advanced technology’s impact on financial markets. Artificial intelligence, for example, can enable a trader, financial analyst or even an ordinary person to predict the volatility of the stock markets and even specific stocks. That comes with advanced technology systems that are designed to monitor social media and news sources.

One such system, called Vector, tracks social media and news coverage of specific trends, companies, stocks, even personalities and returns information that can assist its user in making crucial financial moves.

So, the question becomes, could some of these advancements in processing power drive a “zero volatility point” in financial markets?

End of Moore’s Law? Some of the rhetoric on the matter refers to the end of Moore’s Law.This references the chip in most, if not all, computer processing systems.The big question seems to be, how much longer can the developers go before the chip reaches its limits in terms of size and speed?

Sophie Wilson, designer of the original Acorn Micro-Computer in the 1970s and later developer of the instruction set for ARM’s low-power processors that have come to dominate the mobile device world, has such thoughts, reports NextPlatform.com: “When Wilson talks about processors and the processor industry,

people listen.Wilson’s message is essentially that Moore’s Law, which has been the driving force behind chip development in particular and the computer industry as a whole for five decades, has hit its limits, and that despite the best efforts by chip designers around the world, the staggering gains in processor performance over that time will not be seen again.”

She goes on to say, “that since Intel founder Gordon Moore introduced his prediction in 1965 that the number of transistors in a processor would double every two years – it later was amended to every 18 to 24 months – the IT industry has been on a relentless march to fulfill that prophecy, with significant success. She said that in her lifetime, the performance of computers has increased by a factor of 10,000, due in large part to the continual shrinking of transistors on chips.”

Chip designers can’t keep this up, some say, because the industry found out about 10 years ago that it couldn’t keep increasing chip performance with faster speeds because the processors get too hot. In fact, Intel’s Pentium Pro neared the point of being as hot as a hot plate. Ouch!

That didn’t really stop chip developers, as they sought out other methods of enhancing performance, such as adding multiple processing cores.That worked for a while, but even adding processing cores is reaching its limits, reports Next Platform.

Here’s the thing: At some point, how fast those financial gurus can receive and process financial reports, world news (such as elections, which can heavily impact financial markets everywhere) and plain old tips and instinct, will level off, and that could mean a volatile market.

But the News Isn’t All That Bad Advancements in artificial intelligence (AI) and alternative solutions such as quantum computing, protein computing, DNA computing (data storage), logic gates and Nano machines, may provide

money managers and researchers with new tools to not only read and interpret data at phenomenal rates, but to render precise predictions of all asset classes at once.

“Quantum computers use qubits to store 0s and 1s that are encoded in two distinguishable quantum states, and process them simultaneously,” explains Jo Fletcher, co-founder and chief marketing officer of Vector. “As a result of the aforementioned superposition, quantum computing may facilitate deep learning and data processing capabilities that may far surpass today’s standards.”

Sure, having a savvy business head, experience and even instinct will remain important, but a lot of the guesswork could be cut out, as more and more accurate information is processed and better predictions are created through modes such as quantum computing.

“Imagine a world where analysts are no longer responsible for performing analysis on one sector or asset class at a time. Instead, they cover all asset classes at once because of the ability to process all known financial information at hyper speed,” says Anton Gordon, co-founder of Indexer.me.

Now factor in artificial intelligence and there is a distinct possibility of a zero-volatility point. This would be a point where all known and previously unknown financial market data could be f actored into shor t-ter m and intermediate-term trades.

What Does It All Mean?

Gordon explains it like this:“The very nature of how we trade stocks and other assets will change. As the use and application of quantum computing normalizes in the financial services industry, we may reach a ‘zero-volatility point.’ This is a point in which the returns on various asset classes approach the risk-free rate due to market prices that more accurately reflect current future expected information on the underlying assets.”

In other words, in the future, quantum computing could allow for perfect market information. The possibilities are, quite frankly, staggering. ORMS Carol Ozemhoya is a contributing editor at Vector (https://indexer.me).

June 2017

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Scott Shanaberger (fourth from left), chief operating officer at Holiday Retirement, and the Edelman Award-winning team celebrate at the Edelman Gala.

Holiday Retirement receives Edelman Award Senior living communities firm wins “Super Bowl of O.R.” thanks to revenue management, unique application, benefit to residents.

By Peter Horner

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Given today’s hyper competitive economy, is there any concept more important to commercial companies than having the right product or service at the right time at the right price? We emphasize price because since the dawn of revenue management (RM) in the airline industry in the 1980s, optimal pricing has been a sweet spot for operations research/management science/ analytics, a sweet spot that has grown exponentially in the big data era as new industries discover its power and potential to boost the bottom line.

The holy grail of RM is finding an optimal price point that benefits both companies and consumers. For example, consider the inspiring case of Holiday Retirement, the largest private owner and operator of independent senior living communities in the United States with more than 300 facilities and approximately $1 billion in annual revenue.

Holiday partnered with Atlanta-based firm Prorize to analyze, develop and implement the first RM system in the senior living community industry, creating a revenue gain of $85 million for the first two years of deployment – a 9.3 percent boost on average – with an estimated increase of $304 million for the initial five-year period. ormstoday.informs.org

After extensive pilot testing and analysis, Holiday rolled out the system, Senior Living Rent Optimizer (SLRO), to the rest of its properties in August 2014.

Beyond the initial five-year period, SLRO is estimated to deliver a sustained annual revenue of $88 million.

The impressive O.R. work combined with the unique application and the incalculable benefits to resident clients in terms of customized care resulted in another benefit for Holiday: the 2017 Franz Edelman Award from INFORMS for outstanding achievement in applied operations research, management science and analytics.

The prestigious Edelman Award, considered the “Super Bowl” of O.R. practice, was presented at an Oscar-like gala held in conjunction with the INFORMS Conference on Business Analytics & Operations Research in April in Las Vegas.

“This recognition is the realization of the hard work and collaboration of many people at both Holiday and Prorize in harnessing the power of operations research to transform our senior living operations and business model,” said Scott Shanaberger, chief operating officer at Holiday Retirement.

In accepting the award, Shanaberger indicated Holiday will donate the $15,000 prize money to the Alzheimer’s Foundation of America, a remark that drew loud applause from the packed ballroom at Caesars Palace.

The Problem, People and Project As Holiday officials noted in their Edelman award-winning presentation, an accelerated rise of the aging population is fueling the dramatic growth of a multibillion dollar industry focused on building, owning, operating, buying and selling senior living facilities.These facilities fill a key chasm between living at home and being in a hospital, and range from independent living and assisted living communities to nursing homes.

For senior living facilities to be a successful component in caring for seniors, the communities must be efficiently run and supported by a profitable business model. No process is more foundational to that goal than the way an operator makes pricing decisions.

However, the pricing process of most senior living firms is archaic at best – inconsistent, manual and reactive.These practices create a situation where the local sales staff has frequent requests for exceptions, leading to time spent negotiating prices, first between local and corporate staff, and then between local sales people and residents.

Holiday management recognized its conventional approach to pricing was challenging for everyone and left revenue on the table. That led to Holiday’s partnership with Prorize and the development of the SLRO, a state-of-the-art system that enables a consistent and proactive pricing process

Five other Edelman finalists Along with Holiday Retirement, this year’s Edelman Award finalists included: • American Red Cross for “Analytics-based Blood Collection Methods” • Barco for “Platform-based Product Development” • BHP Billiton for “Detailed Integrated Capacity Estimate (DICE) Model” • General Electric (GE) for “RailConnect 360” • New York City Department of Transportation for “Off-Hours Delivery (OHD) Program”

across Holiday’s senior properties, while simultaneously providing optimal pricing recommendations for each unit in every one of its communities.

The SLRO represents a reliable and credible method of measuring system performance by live pricing experiments, comparing the results from a set of “pilot” communities that used recommendations from the RM system with results from “control” communities that did not use the system.The results showed that the RM system would provide a revenue benefit to Holiday on an average of 9.3 percent (ranging from 4.1 to 16.2 percent based on different baselines).

SLRO, based on innovative pricing science modules and processes, is a complete, interconnected software package with complex sets of interactions and flows. SLRO considers: how data is processed, the kind of variables derived and calculated at approximate levels, how they coalesce to produce an accurate forecast in a low-volume business, the use of a forecast range versus a single point value, the use of a stochastic optimizer to consider most probable demand scenarios, and how workflow is designed to process pricing recommendations.

The SLRO system gives Holiday control over its corporate pricing process, eliminates inventory devaluation and maximizes long-term revenue. In addition, the system is a cultural difference-maker. It has raised Holiday’s organizational “pricing IQ” and given its sales people the confidence that the listed price is the “right price.”

Holiday management recognized its

conventional approach to pricing was

challenging for everyone and left

revenue on the table.

That led to Holiday’s

partnership with Prorize

and the development of the SLRO.

Holiday Retirement COO Scott Shanaberger.

June 2017

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Edelman Award For the first time, operations research brought revenue management techniques commonly practiced in other industries to the senior living industry and did so with great success. Holiday views this project as its most important initiative to date.

“We couldn’t be more proud of this recognition by INFORMS and our work with Holiday Retirement,” said Ahmet Kuyumcu, co-founder and CEO of Prorize. “Our team worked tirelessly to create a world-class solution for senior living and other rental-revenue industries. The results at Holiday Retirement prove that revenue management is transformational to a company’s bottom line.”

“Prorize dramatically changed our business in ways that have truly impacted our employees, our customers, our communities and our shareholders,” Shanaberger added. “We now have control over our corporate pricing process, eliminating inventory devaluation and maximizing long-term revenue.”

The Holiday Touch Throughout their competition presentation, members of the Edelman-winning team often referred to the “Holiday touch” – the human side of the business and the company’s dedication to the aging population it serves.

“When you go into our communities and you talk about the Holiday touch, it means we offer a lot more than just a place for people to live,” Shanaberger said moments after accepting the award.“We care for our residents.We feed them three meals a day.We provide light housekeeping, transportation and in our assisted living communities, we provide care, med management and memory care.That’s when I got emotional on stage.

“Memory care is the most intensive service that we can provide to our residents. They’re not really residents at that point to me.They are fragile human beings, and sometimes when people move into our communities, we’re all they have.We are their family, we are their community.We take it very seriously.”

When asked about the Edelman-winning work, Shanaberger said the benefits “aren’t just for the company; it’s for our residents as well. It’s a mutually beneficial situation. It’s not about just increasing rate.

Sometimes it’s about decreasing rate.What is the best way we can offer the best care at the right price for the residents? A lot of companies get greedy; they want high occupancy and rate.You can’t get both.

That’s what revenue management is all about. This isn’t about charging the most. It’s about what is the right price given the current economic environment for each resident.”

U.S. Air Force and Disney receive the 2017 INFORMS Prize The U.S. Air Force and The Walt Disney Company both received the 2017 INFORMS Prize for their pioneering and enduring integration of operations research (O.R.) and analytics programs into their organizations. The prizes were presented at the INFORMS Conference on Business Analytics & Operations Research in April in Las Vegas.

The INFORMS Prize honors effective integration of operations research into organizational decision-making. The award is given to organizations that have repeatedly applied the principles of O.R. in pioneering, varied, novel and lasting ways.

The U.S. Air Force launched its operations research program in 1942, which has since grown to include approximately 539 military and 849 civilian operations research analysts serving in nearly 300 Air Force organizations and agencies. The diverse applications of O.R. span operational effectiveness, acquisition of new systems, cost analysis, manpower and personnel, along with logistics and infrastructure. Air Force analysts provide timely, credible and defendable analyses that have been and continue to be essential to informing decisions.

“The Air Force’s commitment to operations research was forged 75 years ago in the urgency of World War II and continues today,” says Kevin Williams, director of Air Force studies, analyses and assessments. “We continue to drive analytical innovation and excellence as we address the challenges of the future in nearly every facet of the planning and execution mission of the United States Air Force.”

From improving the consumer and guest experience, to creative content development and operational excellence,

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The U.S Air Force (left side) and The Walt Disney Company (right side) both received the 2017 INFORMS Prize.

The Walt Disney Company uniquely leverages diverse analytic applications to create innovation and value across nearly every system and organization within the company.

In addition, Disney brings together analytics professionals and industry leaders to connect and share best practices to advance the field as part of an annual conference.

“Driven by our desire to create, innovate, learn and inspire, we use analytics and data to enhance our business in unique ways,” says Mark W. Shafer, senior vice president, revenue & profit management, The Walt Disney Parks and Resorts. “At Disney, we’re storytellers, and analytics have become part of our story and will ensure we continue to create magic for years to come.” ORMS ormstoday.informs.org

As for winning the Edelman, Shanaberger said it was a “huge honor,” adding that “many years of hard work went into this and it’s definitely paid off, not just in the award but in terms of how it’s complemented our business.”

So what does Shanaberger think about the power of operations research now that his company has won the Edelman? “Honestly, full disclosure, I did not know what operations research was until we started doing all of this, but I’ve been a part of it for years. I just didn’t know it was O.R. I certainly have a greater appreciation for it today.”

The Judges, Coaches and Emcee The Edelman Award is a nearly yearlong competition that begins with a call for nominations, followed by a vetting and verification process. Once the nominations are culled to six finalists, the competition culminates each spring with presentations before a panel of judges at the INFORMS Conference on Business Analytics and Operations Research. After listening to the presentations and questioning the presenters during a series of sessions, the judges confer behind closed doors to select a winner.Their decision is announced in dramatic fashion by the president of INFORMS, in this case Brian Denton, at the Edelman Gala that same evening.

So what put Holiday over the top in a highly competitive and diverse field of Edelman finalists (see sidebar)?

“They were precise.They knew exactly what they were doing.They had a goal that was very, very valuable to an industry concerned with an aging population that is growing at a rapid rate,” said Leon Schwartz, a longtime member of INFORMS who’s been involved in many Edelman competitions over the years.“Along came O.R. and gave them revenue management to not only raise their own revenues, but it was also able to help them take better care of individuals, older people, the way they should be taken care of.

“Their presentation was terrific. Everything was data-driven.They ran a well-engineered pilot test to see how effective it was before they implemented the solution system-wide. Everything was done to benefit both the company and the residents.”

Edelman Committee chairwoman Anne Robinson, executive director of Global Supply Chain Strategy, Analytics and Systems at Verizon, called the Holiday’s winning work a “game-changer.”“This had all the dimensions of the classic Edelman winner – the impact, the C-level support, transportability. In addition, it had the novelty of the application. It was a bit of a Cinderella story, but certainly a well-deserving recipient of the prize.

“This is more than revenue management,” Robinson continued.“In reality, it was about taking the cost piece out of the conversation and allowing their retire-

ment facilities to start having discussions about what are the amenities that mean the most to the person potentially impacted. It was a game-changer between the potential client and the sales force. Instead of being about dollars and cents, it was really about what’s important as the client considers retirement complexes and the various amenities.”

Summing up the judging process, Robinson said, “It was an interesting night.

We had a very diverse set of applicants this year, and all of Master of Ceremonies Mike Trick. the finalists were outstanding.

It was a very difficult decision. It took us a lot of “There are time to come up with our decision, but I’m super pleased with where we landed.”

Needless to say,Arnie Greenland, who coached the Holiday team along with Jeff Alden in preparation for the competition and the presentation, agreed with the judges’ assessment.“This was a great team that worked really hard and had a great message,” Greenland said. out there, “The core of their message was it was a new area for and we operations research, an area that wasn’t historically understanding and ready for these kinds of tools and methods. It was a very complicated change management challenge in addition to the analytic challenge, the and they pulled it all together.”

Asked to expand on the team’s winning message, Greenland said it was clear from the presentaThat part is tion and the goal of the O.R. work that Holiday was dedicated to the senior community it serves. “It’s not fun.” just about optimizing revenue; it’s about making the right decisions and taking a lot of the pain out of a – Mike Trick really difficult time in people’s lives when they go through transitions,” Greenland said.

Mike Trick of Carnegie Mellon University, a past president of INFORMS and a past chair of the Edelman Award Committee, put in a masterful performance as master of ceremonies for this year’s Edelman Gala.Asked to sum up the evening, including the Edelman and a handful of other awards presented at the gala,Trick said,“It’s been great, just seeing all these schools and companies doing such fantastic stuff, and it’s really the tip of the iceberg.There are many amazing projects out there, and then we get to see the very best.

That part is really fun, along with seeing more than 800 people in the audience. It really does show the ongoing growth of our field and all the excitement, particularly around analytics.” ORMS

many amazing projects

get to see very best. really

Peter Horner (peter.horner@mail.informs.org) is the editor of OR/MS Today and Analytics magazine.

Sources: INFORMS, Holiday Retirement and Prorize.

June 2017

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The road best taken: A new toolkit for multi-criteria decision-making.

Image © Сергей Тряпицын | 123rf.com

Models that are never wrong New tools for multi-criteria decision-making return control to the decision-maker

By Ignacy Kaliszewski and Douglas A. Samuelson

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A new toolkit for multi-criteria decision-making (MCDM) offers a possibility most OR/MS practitioners consider impossible: models that are never wrong. George Box’s famous proclamation, “All models are wrong, some are useful” prevails, but we suggest an alternative idea: Many models are not so much wrong as ill-conceived.

One major reason for this is that in every practical decision problem, there are multiple desired aspects, but the traditional single-criterion optimization approaches collapse the trade-offs into one objective. Perhaps there are also a number of constraints, but in all cases the model structure imposes a single, pre-specified set of tradeoffs. Although multiple-aspect/multiple-criteria problem framing has grown in popularity, beginning in the 1970s, its use has still lagged far behind the emphasis – in our view, over-emphasis – on single-criterion optimization. (It is not widely remembered now that the famous KuhnTucker optimality conditions applied originally to multi-criteria problems [1].)

Moreover, the benefit of MCDM has not been readily apparent, because the MCDM (also known as multi-criteria decision analysis, or MCDA) domain offers so many different approaches and methods, all very elegant and far reaching, but too little guidance in how to apply them.

MCDM Essentials in Ready-to-Use Tool Now, however, we have the essentials of MCDM extracted in the form of a tool, ready for use in any decision problem which occurs in practice.The new work [2] by ormstoday.informs.org

the first author of this article refers to a generic model that consists of a set of admissible decision variants and their multi-aspect valuations.This is an implementation and extension of earlier theory [3]. The newsletter of the International Society on Multiple Criteria Decision Making, available free of charge to the members (no membership fee), is an excellent source of the current research in the domain.

In the generic model, the admissible set is a proper subset of the set of all possible decision variants – that is, the admissible set corresponds to the feasible region in traditional optimization. Essential aspects of the problem, for which an admissible (decision) variant selected as the most preferred variant should have favorable valuations (appraisals, characteristics), become criteria (alternatively: objectives).To be able to harness computers for computations to the model, we need numerical valuations (dollars, tones, etc.). Then, we can valuate variants by criteria (objective) functions.Without loss of generality and to ensure consistent exposition, we assume for this article that all valuations are in the form of the more the better.

The set of rational candidates for the most preferred variant to a decision problem fitting to this model consists of admissible variants that are efficient (i.e., they are not dominated by any other admissible variant with respect to criteria valuations).That is, there is no other admissible variant that for all criteria valuations is as good as the former and for at least one criterion valuation is better; for instance, worker A, as qualified as worker B but less productive, is dominated by B.Thus, we arrive at a Pareto frontier: a set of choices with the property that we cannot move from one choice to another to make ourselves better off in some way without making ourselves worse off in some other way.

None of these choices is universally or objectively better than any other. To select the admissible variant that the decision-maker (DM), individual or collective, considers as the most preferred, he or she can be assisted, but not dictated, by the model.

Rather, the model (or models) identifies a number of sets of possible decision admissible variants and the consequences of choosing them, and the DM then – and only then, not at the beginning of the modeling process – exercises his or her final preference.

Why the Model is Never Wrong In this class of analyses, the question of whether the model is wrong or correct is immaterial. In fact, there is not just one model. Following the Herbert Simon four-phase decision-making scheme [4], there is a sequence of models, each tentative, representing a temporal DM’s problem perception. The four phases – intelligence (of the problem), design (of the model), choice (of the most preferred variant) and overview (whether the most preferred variant fits the reality) – are closed in a cycle forming the learning

loop. Cycling goes until the DM chooses. The last model in the sequence is, subjectively and temporally, correct for him or her.The DM, the sovereign of the decision process, is not a part of the model. Usually, what the DM needs is assistance in the choice (third) phase, specifically a clear evaluation of the likely consequences of the offered choices.

To illustrate via a simple example, suppose that a ship captain, using old charts and outdated navigation methods, wants to ply trade routes along a coastline with many bays and estuaries. He knows a few ports of call where he could trade profitably. Formulating his route choice in traditional ways, he might, to limit the risk of running into hazards, constrain his route not to deviate from the line connecting those points – and miss many opportunities to enter harbors where profitable trade could occur.To put it mathematically, he has wrongly assumed that the feasible region is convex and continuous, so he can find high-value points by linear interpolation between the good points he knows.

However, given a less accommodating feasible region, those new computed high-value points turn out not to be reachable, and his linear methods won’t tell him where the best feasible point is for the compromises he would prefer to make.With this improved method, the captain can learn of estuaries not on his smooth interpolation line and then find, case by case, high-value actions that reflect how much risk and extra effort and expenditure he is willing to accept, given the potential profit and the attractiveness of alternatives.

Here comes the time for the

DM to act: “I say! If (to get an

admissible variant) I have to

make concessions versus the

ideal valuation, let this be on

my terms!”

Here’s How It Works For each criterion function taken individually, the best value, i.e., the maximum (as assumed above) over admissible variants is calculated. If there exists an admissible variant that maximizes all criteria functions simultaneously (this happens, but not often), then this variant is clearly the most preferred, and this terminates the decision-making process. Indeed, the valuation of this variant with respect to all criteria is the best possible. Such variant is called ideal.

If the ideal variant does not exist, one is still left with the ideal valuation. Despite that the ideal variant does not exist, the ideal valuation is a valuable information to the problem:What is the best we could possibly do under ideal conditions that do not exist? Comparison to this value enables us to see how much the valuation of any admissible variant, an efficient (i.e., not dominated) variant in particular, represents a concession (or sacrifice) versus the ideal valuation. And here comes the time for the DM to act: “I say! If (to get an admissible variant) I have to make concessions versus the ideal valuation, let this be on my terms!”Those terms are represented by a vector of concessions with as many components as the number of criteria, all positive. (Any concession costs something; that’s why it’s a concession.) From these choices, we construct the June 2017

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Multi-Criteria Decision-Making When

applying the tool, the DM

sets his/her temporal (trial)

preferences and is

provided with the

respective variant reflecting

compromise half line, a set of possible (not necessarily admissible) decisions variants that preserve the ratio of trade-offs the DM is willing to make among criteria as we move away from the unattainable ideal.

To adhere to the temporal DM’s preferences represented by the vector of concessions, one should search for valuations of efficient variants on the compromise half line, using a construct that always yields a single number variant valuation of an efficient variant. One such construct is the weighted linear function, the sum of weighted objective functions (weights positive). Given weights, this function is maximized over the set of admissible variants only by efficient variants with valuations on hyperplanes tangent to the set of admissible variants. Except for a few very specific problems, such as the linear ones, this formulation begins by excluding some efficient variants from consideration.

They cannot be derived by the linear weighted function and thus they are a priori excluded from potential candidates for the most preferred variant.

Valuation of Variants To avoid a priori exclusion of some efficient variants from considerations, we have to use another function to express the valuation of variants we are considering.

The weighted max function is a suitable choice. Rather than using the weighted linear objective function that imposes a linear structure, we use a more general combination of the proposed concessions. Once the vector of concessions t is provided by the DM, we compute the weights of the max function so as to move along the compromise half line, shown as q in the figures, descending from the ideal valuation ŷ, or as close to the compromise half line as possible if the compromise half line contains no efficient variants.

Then, taking the minimum of the weighted max function with these weights over the set of admissible variants, yields an efficient variant which: – if the compromise half line crosses the set of efficient variant valuations, then the valuation of that variant lies on the compromise half line (Figure 1).

these preferences as the

nature of the problem

yˆ

. .................. .• . ... ... ..... . ... ..... . . ..... . y .•...... . . ... .... . .... ......... ............ .................... ....... ........ . ........ ........ . . ..... . ... .... . .. . .. .. . . . ... . . ... ... . . . . ..... . . . . ................... Θ. .

criterion 1

Figure 2: The case where the compromise half line Θ misses Figure 2: The case where the compromise half line q variant valuations (and hence misses the set of efficient variant misses an infinite set of variant valuations (and hence contour of the weighted max function at the valuation y of an misses the set of efficient variant valuations); the is shown (dashed line).

contour of the weighted max function at the valuation ŷ of an efficient variant is shown (dashed line). criterion 2

Θ...

.

• y •.....

• yˆ

•

•

..

•

.

.

.

.

.

.

.

.

. . . . . .... ........ ....... .

•

criterion 1

Figure 3: The case where the compromise half line Θ misses a variant (and hencethe misses the set ofhalf efficient Figurevaluations 3: The case where compromise line variant val contour of the weighted max function at the valuation y is shown ( q misses a finite set of variant valuations (and

hence misses the set of efficient variant valuations); the contour of the weighted max function at the valuation ŷ is shown (dashed line).

Moreover, for any efficient variant there are weights for which taking the minimum of the weighted max function over the set of admissible variants yields this variant. Thus, no efficient variant is a priori excluded.

In contrast to the weighted linear function, this construct is general and hence works for any decision problem, irrespective of its properties such as linearity, differentiability, continuity, discreteness and so on.

Besides yielding a fair, egalitarian, efficient variant, the weighted max function has another merit. Namely, it is built on differences between what is ideal and what is 1 criterion 2

actually achievable, thus it refers to the lost (unachievable • yˆ though) opportunities, i.e., in terms of losses. If Tversky ........... ....... ..•...... ..... and Kahneman [5] were right in concluding that peoy ..... .... ........ ...... Θ ...... ple give more attention to losses that to gains, then the . ... ... .. ... . weighted max function is, again, a better decision assisting .... . . . ..... ... ........ construct than the weighted linear function, as DMs relate .......................... more readily to forgone losses than to possible gains.

criterion 1 To summarize, when applying the tool, the DM setsthe his/her (trial) preferences and is provided Figure 1: The case where the compromise half line Θ crosses set oftemporal vari1: Theatcase where the compromise half line antFigure valuations some valuation y of an efficient variant; the contour of the variant reflecting these preferences with the respective corresponding weighted max function at y at is shown q crosses the set of variant valuations some (dashed line).

– strictly or only closely – as the nature of the problem valuation ŷ of an efficient variant; the contour of the dictates.The DM repeats this till he or she is satisfied. corresponding weighted max function at ŷ is shown 1 There is not much decision-making support (dashed line). for the DM in this tool (which by no means is an – otherwise, the valuation of that variant lies off algorithm), and this is the price for its generality. the compromise half line (Figures 2 and 3).

Typical MCDM/MCDA models offer much more

dictates.

.

26 | ORMS Today

criterion 2

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June 2017

.

.

.

.

.

.

.

.

.

.

. . . .... . . .. . . ... . ....... ....... .......

.

ormstoday.informs.org

than that, but if one goes for more, things get complicated. On the other hand, the tool enables a quick start for a beginner or a casual user. In any case, the tool can serve as a common language for multi-aspect perspectives across O.R. applications.

The Tool Consider a decision problem with two criteria (the tool works for any number of them). The nature of the set of admissible variants, for example, could be composed of variants given explicitly, portfolios of indivisible items (e.g., portfolios of projects) or portfolios of divisible items (mixes of items in specific proportions). The whole decision process takes place in the space of valuations. After the ideal valuation is derived and assuming that the ideal variant does not exists, the DM’s “playground” is as shown in Figure 4.

Analysis After considering the valuation, DM decides that he or she would prefer to compromise on criterion 1 less than criterion 2, yielding the slope of the compromise half line.

Compromising, option 1.

To satisfy this preference, the DM sets the first component of the compromise trade-off vector of concessions t relatively low to the second, reflecting more willingness to compromise on component 2 than on component 1.

Compromising, option 2.

The DM provides a trial (reference) valuation which reflects this revised preference.

Go back to Derivation step.

Repeat until DM is satisfied.

Conclusions New research has produced a short, readily usable guide to a tool that makes implementation of criterion 2

MCDM much more usable by practitioners. The ˆ availability of this tool can enable a revolutionary ....... ......• . ....... ....... ....... ....... ....... .......• y . ... change in the support of decision-making: letting the .... . decision-maker interactively choose desired trade-offs .... ”The playground” ... among competing objectives and presenting him/her . ...

•... the corresponding actions, subject to realism about . what is feasible.This approach is much closer than the

traditional single-criterion optimization to the way criterion 1 most decision-makers actually prefer to make choices.

Figure 4: The DM’s ”playground” once yˆ is derived.

It also neatly avoids the common phenomenon of Figure 4: The DM’s “playground” once ŷ is derived. developing models that are wrong because they fail If the DM opts for any of two valuations (and the to address trade-offs and competing objectives in the corresponding admissible variants) derived to establish appropriate way. Learning this new approach promises ŷ, it means that he or she opts for no concessions to yield substantial benefits for both researchers and on the best value of the first or the second criterion. practitioners – and their clients. ORMS Otherwise, concessions on ŷ are inevitable.The process Ignacy Kaliszewski (ignacy.kaliszewski@ibspan.waw.pl) is for selecting the most preferred variant is an iterative a full professor of the Systems Research Institute of the Polish Academy of Science, Warsaw, Poland, where he earned his procedure (till he or she exclaims BINGO!). Here is Ph.D. and Habilitation (the second scientific level degree). one iteration of it with a hypothetical DM’s behavior: He has extensive consulting experience along with his Derivation of an efficient valuation (and the distinguished record of academic research. corresponding variant) Douglas A. Samuelson, D.Sc., is president and chief A valuation of an efficient variant is derived scientist of InfoLogix, Inc., a small R&D and consulting (Figure 5). company in Annandale, Va. He is a contributing editor of criterion 2

Ignacy Kaliszewski is the author of the book, “Multiple Criteria Decision Making by Multiobjective Optimization: A Toolbox.”

OR/MS Today.

• Θ. . . . .

... .

. ... . . . ....... .......

◦

Θ . . .

• y¯

.

• yˆ

REFERENCES

. . .. . . . . . ... . . . ... . ....... .......

◦

1. Kuhn, H.W., Tucker, A., W., 1951, “Nonlinear Programming Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability,” pp. 481-492, University of California Press, Berkeley, Calif.

•

2. Kaliszewski, I., Miroforidis, J., Podkopaev, D., 2016, “Multiple Criteria Decision Making by Multiobjective Optimization: A Toolbox,” Springer.

3. Kaliszewski, I., 2006, “Soft Computing for Complex Multiple Criteria Decision Making,” Springer.

Figure 5: Two efficient valuations (circles) derived with the weighted max func5: lines Two efficient derivedτ (defining Θ) provided tion Figure (dashed representvaluations contours) (circles) for: 1. vector 4. Simon, Herbert A., 1977, “The New Science of Management Decision,” Prentice-Hall: with 2.thevector weighted max function (dashed lines via a trial point Θ ) provided indirectly, y¯. directly, τ (defining New Jersey.

criterion 1

represent contours) for: 1. Vector t (defining q) provided directly, 2. vector t1 (defining q1) provided indirectly, via a trial point ŷ.

5. Tversky, A., Kahneman, D., 1974, “Judgment under Uncertainty: Heuristics and Biases,” Science, New Series, 185, 4157, 1124-1131.

June 2017

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EDITOR’S NOTE: An article in the February 2014 issue of OR/MS Today described enterprise optimization as “a framework that seamlessly integrates management accounting’s principles with significant advantages for managers.” The article outlined two management accounting principles required to achieve enterprise optimization: 1) the causality principle (i.e., cause and effect modeling), and 2) the analogy principle (using cost information to accurately reflect operational business activities) [1]. That article was an elaboration on an earlier article, “A Managerial Costing Conceptual Framework” published by IMA in March 2013 [2]. However, neither article described any specific enterprise optimization applications. That is the purpose of this article.

OIS represents the first time OIS’ analytics, both of which are in widespread use today, have ever been integrated.

Image © Sergey Nivens | 123rf.com

Enterprise optimization: a new application The demand-driven operational income statement (OIS) integrates prescriptive optimization and predictive analytics.

By Alan Dybvig and Gary Cokins

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June 2017

The demand-driven operational income statement (OIS) application integrates two advanced analytic techniques: prescriptive optimization (i.e., what is the best possible outcome?) and predictive analytics (i.e., what will happen if we do X?). OIS employs optimization, to the best of the authors’ knowledge, for the first time to financial flow variables (i.e., the income statement) and not, as traditionally been the case, to the stock variables of the balance sheet [3]. This is important because as Randall Bolton comments in his book, “Painting with Numbers,” the income statement is “The one report every organization needs.” In fact, he devotes an entire chapter to it.

In addition, OIS represents the first time OIS’ analytics, both of which are in widespread use today, have ever been integrated, specifically, Operations (i.e., supply chain network design) and Sales/Marketing (i.e., marketingmix modeling). The former makes OIS operational and the latter makes OIS demand-driven. ormstoday.informs.org

The result, with Finance’s leadership and featur ing Sales/ Marketing’s analytics as the driving force, is a powerful, new form of the income statement, one that assures important cross-functional performance management benefits for the entire enterprise.

Overview of the Master Budget Revenues Budget

Production Budget

Current Applications Direct Direct Manufacturing Manufacturing Materials Overhead Budgeted income statement. As Labor Costs Budget Costs Budget Costs Budget illustrated in the master budget flow chart in Figure 1, the traditional Cost of Goods Sold Budget income statement is developed from the budget, beginning with the OPERATING revenues budget (forecasted level of BUDGET R&D/Design Costs Budget unit sales) as the starting point.

M a r k e t i n g - m i x m o d e l i n g.

Traditionally, demand is the critical Marketing Costs Budget independent variable in the annual planning process. As illustrated in Figure 1, it is demand as expressed Distribution in the forecast that drives the process.

Costs Budget However, the essence of marketingmix modeling is the opposite, where Customer-Service demand is treated as a dependent Costs Budget variable driven by sales and marketing expenditures.

Administrative One of the authors first Costs Budget encountered the marketing-mix modeling concept more than 10 years Budgeted ago while doing research for what has Income Statement become the product that creates the OIS. The article, by John D.C. Little, FINANCIAL describes an online model for use Budgeted Budgeted Capital Cash BUDGET Statement Balance Expenditures by product managers on advertising Budget of Cash Flows Sheet Budget budget questions [4]. The objective was to size and allocate advertising Adapted from Charles T. Horngren, George Foster, and Srikant M. Datar, Cost Accounting (New York: Prentice Hall, 2000) expenditures, and the model was called, appropriately, ADBUDG. Figure 1: Overview of the master budget.

In the article, Little describes the data required for generating the “sales response to advertising function” and its shape. Now referred to as response functions, they are now Interestingly, the mathematical expression in this quantitatively developed [6] and have become more model remains the most common one 35 years later, accurate for the following reasons: though for reasons discussed below the data are no 1. Availability of more accurate and complete longer qualitatively developed. data on sales (e.g., scanner data at checkout provided Several people then went on to extend Little’s by firms like IRI and Nielsen) and tracking of activwork to other promotional elements than advertisities (e.g., digital promotions) ing. For example, Lodish, et al. extended it to the 2. Vastly improved computing power sales force in an article titled, “Sales Force Sizing and 3. Individual promotional elements of total Deployment using a Decision Calculus Model at sales and marketing expenditures extended to Syntex Laboratories” [5]. include more than one element (e.g., print, TV, Since their original formulation, Little’s “Sales digital, sales force) Response to Advertising Functions” have become 4. Individual sales and marketing elements increasingly more powerful and more sophisticated. extended to include econometric ones (e.g., June 2017

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Enterprise Optimization

Supply chain networks must be

re-evaluated on an

ongoing basis to balance revenue growth, costs,

working capital, asset deployment and

sustainability objectives.

weather/environment, economic, industry trends and competition) These decision calculus applications are now broadly referred to as marketing-mix modeling (MMM). MMM is defined in Wikipedia as, “Marketing mix modeling (MMM) is statistical analysis such as multivariate regressions (predictive analytics) on sales and marketing time series data to estimate the impact of various marketing tactics (marketing mix) on sales and then forecast the impact of future sets of tactics. It is often used to optimize advertising mix and promotional tactics with respect to sales revenue or profit.”

Details of the current state of marketing-mix modeling efforts can be found in IRI’s brochure, “Success and Failures in Marketing-Mix Modeling” [7]. Details on the use of marketing-mix modeling techniques, focused exclusively on the sales force, are available in the article, “SalesForce Decision Models: Insights from 25 years of Implementation” [8].

Supply chain network design. Supply chain network design is a key business function that has increasingly gained the attention of senior management. Modern supply chains are complex global networks of suppliers, manufacturing and distribution facilities, ports, third-party providers, transportation choices and inventories that are impacted by rapidly changing market conditions, competitor initiatives, disruptions, currency fluctuations, regulatory issues and so on. Supply chain networks must be re-evaluated on an ongoing basis (at least annually) in order to balance revenue growth, costs, working capital, asset deployment and sustainability objectives.

Remarkably, even today many executives equate supply chain strategy with the number, location, size and mission of distribution centers. This view is shortsighted. Consider the following contemporary list of strategic issues that a network design tool can be used to analyze:

Facility issues

(types: supplier, manufacturing, DC, cross-dock, port) 1. Number, size and location 2. Ownership 3. Mission • raw material supplier procurement volumes, costs and limits; • plant location manufacturing volumes, costs, capacities and inventory requirements; • distribution center throughput and storage levels, operating costs, throughput and storage capacities and inventory requirements; and 30 | ORMS Today

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June 2017

• port, cross-dock and pool throughput levels, operating costs and throughput limits.

Major policy issues

1. Strategic sourcing 2. Target market expansion including international 3. Supply chain vulnerability, capacity, seasonal demand/supply and sustainability measurement and objectives including energy and carbon usage profiles 4. Mergers and acquisitions 5.Transportation policy 6. Inventory strategy 7. Customer profitability and cost-to-serve Because of the all but infinite possible solutions to these design issues, mathematical programming prescriptive optimization techniques are required, in this case a mix of linear and integer programming (MILP).

For more details, the interested reader is referred to “Modeling the Supply Chain,” Chapter 4 [9].

OIS’ Functional Benefits For Finance, OIS: • Creates the maximum profitable forecast displayed in the operational income statement.

• Integrates the executive team’s strategic plan with the annual financial plan (Their strategy is typically disconnected from a traditional budget.)

• Maximizes the projected OIS profit opportunity of a proposed merger and acquisition (M&A) deal.

• Does not disrupt or replace any of the enterprise’s currently installed operational and financial planning and execution software systems (e.g., FP&A, S&OP).

• Improves the forecast process and its results.

• Enables the creation of a flexible OIS. (Definition from Accounting.com: “A flexible budget is a budget that adjusts or flexes for changes in the volume of activity”).This is useful for actual vs. budgeted cost variance analysis [10].

• Enables a strategic OIS to be developed using the same model structure as the annual OIS. This presumes that the firm is comfortable with the accuracy of cost data in the strategic time frame and forecasts for the strategic time frame beyond a year.

For Sales and Marketing, OIS: • Maximizes the return on investment (ROI) of the expenditures by the Sales and Marketing departments. ormstoday.informs.org

Figure 2: Three cost elements used for COGS and G&A.

• Enhances marketing-mix modeling applications for firms that are currently using them.

For Operations, OIS: • Designs the optimally feasible supply chain plan required to make and fulfill continuously revised forecasts respecting sustainability constraints of energy and carbon emissions, if desired.

• Redesigns the strategic supply chain as a part of developing the strategic plan thus making it truly optimal. Most supply chain network designs are sub-optimal because they all assume a fixed forecast of product volumes. As explained in the Model section, the OIS relaxes this assumption.Thus, the OIS supply chain is truly optimal because of the concept of suboptimization [11].

• Possibly, provides an optimal solution for the vexing issues of stock keeping unit (SKU) proliferation and the omni channel [12].

• Is easier to build if the firm has activity-based costing data.

A variety of financial trade press articles confirm the trend of CFO leadership in cross-func-

Figure 2 tional analytics and greater involvement with Operations [13].

The OIS Model The OIS contains three cost elements: 1) all the operations performed by the firm, 2) the buildings within which the operations are performed, and 3) links connecting the buildings. Importantly, since an OIS answers the “best possible outcome” question (in the OIS’ case, the most profitable forecast), then the costs of these three elements must be represented in the model as variables so the model can calculate and select the best outcome from all the possible solutions.These three cost elements are arranged sequentially in echelons from procurement to the customer in a prescriptive mathematical programming model (MILP) as described above.

The three cost elements used for the cost of goods sold (COGS) and general and administration (G&A) operations are referred to as cost functions.

They are a mathematical relationship describing how costs (y axis) vary with changes in the operation’s quantities (x axis) and are an example of single variable (univariate) predictive analytics (see Figure 2).

There are at least four ways for management accounting practices to work with Operations to June 2017

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Enterprise Optimization Unlike

cost functions that will

bring the management accountants

closer to Operations, enterprise

response functions will bring them

closer to

Sales and Marketing.

create these functions: statistics, engineering data, accounting records and, as was only recently utilized by progressive accountants, with activity-based costing data [14].

The final element of an OIS, Sales, is more complicated. These cost relationships are referred to as enterprise response functions. They are an OIS’ third use of advanced analytics and are also Stage 3 in the analytics continuum – predictive analytics.

Enterprise resource functions differ from cost functions; specifically, they reverse the x and y axis relationship of the cost functions. The independent variable, the horizontal axis (x), is the total sales and marketing expenditures, and the dependent variable, the vertical axis (y), is the quantity that those expenditures drive.

Deriving the enterprise response functions often requires much more sophisticated analytics than the cost functions. As discussed briefly above, the amount of demand generated by sales and marketing expenditures are a function of many different factors: prior customer satisfaction with the goods, the amount and effectiveness of marketing, the level of competition, pricing and discounting, external events (like weather), etc. Advanced analytic techniques, such as those used for marketing-mix modeling, are available to estimate the enterprise response functions [15]. Companies will also need to have access to experienced practitioners who can build and validate these models unless the companies already possess a demand signal repository and can implement demand signal analytics. These enterprise response functions are an example of REFERENCES

1. https://www.informs.org/ORMS-Today/Public-Articles/February-Volume-41-Number-1/ Enterprise-optimization 2. http://operationalincomestatement.com/roi/ima-conceptual-framework-for-managerialaccounting-nov-2014/ 3. Cornuejols and Tutuncu, “Optimization Methods in Finance,” Cambridge University Press, 2007.

4. http://operationalincomestatement.com/roi/little-1970-full/ 5. http://operationalincomestatement.com/roi/lodish-1988/ 6. http://operationalincomestatement.com/roi/appendix/developing-enterprise-response-functions/ 7. http://operationalincomestatement.com/roi/wp-content/uploads/2015/05/2009-IRI-marketingmix-modeling.pdf 8. http://operationalincomestatement.com/roi/zs-25-year-review/ 9. Shapiro, Jerry, “Modeling the Supply Chain,” Duxbury, 2001.

10. http://operationalincomestatement.com/roi/appendix/flexible-ois/ 11. http://www.sjsu.edu/faculty/watkins/suboptimum.htm 12. http://operationalincomestatement.com/roi/wp-content/uploads/2015/08/dorenkott.pdf 13. http://operationalincomestatement.com/ 14. http://operationalincomestatement.com/roi/wp-content/uploads/2015/05/cost-function-curvedevelopment.pdf 15. http://operationalincomestatement.com/a-brief-review-of-approaches-for-developingenterprise-response-functions/ 16. http://operationalincomestatement.com/mccoy-results2-2/ 17. http://operationalincomestatement.com/roi/ois-related-articlesWiley

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June 2017

multivariate (more than one independent variable) predictive analytics. A variety of firms are available for assistance with enterprise response function development including ZS Associates, MarketShare, Hudson River Group, Marketing Management Analytics and Analytic Partners.

Unlike cost functions that will bring the management accountants closer to Operations, enterprise response functions will bring them closer to Sales and Marketing. Further, as described above, since the enterprise response function’s dependent variable – cost – is the independent variable in cost functions, then enterprise response functions drive the entire OIS model. Thus, Sales and Marketing’s expenditures are the cause that drive COGS + G&A costs. This is a reality that will elevate the importance of Sales and Marketing’s role in the annual planning process.

A final point needs to be emphasized: the OIS works. A simplified model was created by a consulting firm using data from an activity-based costing system. Its results determined the firm had left 25 percent to 150 percent profit on the table [16].

As an example of enterprise optimization, OIS is well positioned to be of interest to many as a new, powerful form of the income statement, “The one report every organization needs.” Further, it positions the CFO very well in light of emerging CFO leadership trends in terms of advanced analytics and operational matters.

In these times of ever increasing competition, volatility and an uncertain economic outlook, investigating and evaluating whether an operational income statement would benefit organizations should be an imperative. It would likely constitute an enduring competitive advantage. ORMS Alan Dybvig (alan@operationalincomestatement.com) is the managing partner of Dybvig Consulting. His Internet protocol was implemented to create the OIS. Dybvig spent more than 32 years with IBM as a director and senior manager, primarily in supply chain and sales/marketing assignments, and then four years with a Warburg Pincusfinanced supply chain startup where the idea for OIS germinated. He holds a bachelor’s degree in engineering physics from Cornell University and an MBA in quantitative methods from the University of Michigan.

Gary Cokins (www.garycokins.com) is an internationally recognized expert, speaker and author in enterprise and corporate performance management improvement methods and business analytics. He is the founder of AnalyticsBased Performance Management, an advisory firm located in Cary, N.C. Cokins received a bachelor’s degree in industrial engineering/operations research from Cornell University and an MBA from Northwestern University’s Kellogg School of Management.

ormstoday.informs.org

Whatâ&#x20AC;&#x2122;s Your StORy? Rahul Swamy PhD Candidate, Department of Industrial & Enterprise Systems Engineering, University of Illinois Urbana-Champaign INFORMS member since 2014 What prompted you to enter this field? Why? During my undergraduate program in Engineering Physics at IIT Madras, I was exploring ways in which I can apply my math skills to a real-world setting (and get far away from quantum physics). I took a basic course on operations research and that's when I stumbled upon this unique area of mathematics that has a high theoretical as well as applied nature to it.

Since then, I've loved the challenge presented by every new O.R. problem that I have come across so far, and there is no turning back!

How has being a member of several INFORMS communities affected your life/career?

Being part of an INFORMS Student Chapter has been the best part of my graduate school.

As the president of UIUC's Student Chapter, my role in fostering camaraderie in the student community through organized events and bringing together like-minded people has been very fulfilling. I recently attended the INFORMS Student Leadership Conference (April 21-22) in Baltimore, which had Student Chapter officers from around the world. I thoroughly enjoyed the diversity of ideas shared across the Chapters and hopefully we'll be able to use some of those in our own.

How would you apply analytics to grad school life?

Ideally, I want to measure my sleep patterns and find out ways in which I can reduce irregularities both in terms of number of hours of sleep I get as well as the time I go to bed.

I've been recommended to try using a Fitbit, and perhaps one day I will be able to organize my sleep schedule better with real data.

When I graduate, my perfect job would beâ&#x20AC;Ś My dream job would be one that allows me to pursue research in applying O.R. to problems of social value. I also happen to cherish all the teaching opportunities that I've taken upon in my grad school, and I would absolutely love to tie teaching and mentorship to my research activities.

More questions for Rahul?

Ask him in the Open Forum on INFORMS Connect!

http://connect.informs.org

ORSI turns 60 Operational Research Society of India prepares to celebrate milestone in December.

By

T h e O p e r a t i o n a l R e s e a rc h S o c i e t y o f I n d i a ( O R S I ; www.orsi.in), founded in 1957 and dedicated to the advancement and spread of knowledge of operational research (O.R.) in India, will celebrate its “diamond jubilee” on Dec. 21-23 in Kolkata, India. The celebration will be held in conjunction with the 50th Annual ORSI Convention (ORSI 2017), along with an international conference on “Advancing Frontiers in Operational Research: Towards a Sustainable World” (AFOR2017). ORSI welcomes all to attend.

History of ORSI In the decade after India gained independence from Britain in 1947, when the hopes and aspirations of its people were very high, a small group of Indian academicians related to the field of operational research understood the importance of the subject as an effective tool for scientific management in an environment of rapidly increasing demand for resources. This led to the foundation of the Krishnendranath Mitra Operational Research Society of India in 1957 under the able leadership of and Goutam Dutta statistician and professor Prasanta Chandra Mahalanobis of Kolkata, then deputy chairman of the National Planning Commission of India.

ORSI soon became a national forum for researchers and practitioners in the field of O.R. and allied fields. The objective of the society is to enhance the knowledge and promote the study of O.R. within the ranks of academicians and industrial professionals in India. The society gained importance in India by promoting theory and practice in O.R. As a result, the society expanded its presence throughout the country. Today, ORSI supports 16 operating chapters in four metropolitan areas and several mini-metros. It remains headquartered in Kolkata.

In 1959, ORSI became affiliated with the International Federation of Operational Research Societies (IFORS), which opened opportunities for ORSI members to create and share knowledge with O.R. enthusiasts from other parts of the world. In 1985, ORSI was instrumental in the formation of the Asia Pacific Operational Research Societies (APORS), which enhanced the society’s interactions with other O.R. societies of Asia-Pacific such as Australia, China, Japan, Singapore and South Korea.

ORSI addresses its objectives by publishing a quarterly journal World renowned named OPSEARCH (currently managed by Springer India) with statistician Prasanta original papers in O.R. and allied fields and by hosting national Chandra Mahalanobis was and international conferences, workshops and seminars on O.R. the founding father of the Operational Research topics. The society was founded as a meeting platform for O.R. Society of India in 1957. academicians and practitioners and to expand their horizons by

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ormstoday.informs.org

Professor Prem Vrat (third from left) receives an award for his outstanding contributions toward the promotion of operational research in India at last year’s ORSI Convention. The 50th Annual ORSI Conventional will be held in December.

sharing knowledge of theory and practice both inside and outside the country. As part of its 60th anniversary this year, ORSI also will celebrate the 125th birth anniversary of its founding president, P.C. Mahalanobis, by introducing three “distinguished educator” awards in his honor.

The Founder Born in 1893 in Calcutta, Prasanta Chandra Mahalanobis was a renowned statistician and founder of the Indian Statistical Institute. As a prime architect and the first deputy chairman of the Planning Commission in India, he made a remarkable contribution to the field of statistics and operational research. Among his many honors, he received the Padma Vibhushan, the second highest civilian award from the government of India (1968). In addition, he received the Weldon Medal from Oxford University (1944), the Sir Deviprasad Sarvadhikari Gold Medal (1957), the Gold Medal from the Czech Academy of Sciences (1964) and the Durgaprasad Khaitan Gold Medal from the Asiatic Society (1968).

The society

Professor Mahalanobis served as president of the Indian Science Congress in 1950 and as president of the International Statistical Institute in 1957. He was an elected fellow of several societies and academies such as the Royal Society of London (1945), the Econometric Society of United States (1951), the Royal Statistical Society of U.K. (1954), the USSR Academy of Sciences (1958), the American Statistical Association (1961) and was an honorary fellow of King’s College, Cambridge (1959). He also received honorary degrees from the University of Calcutta (1957), Sofia University (1961) and the University of Delhi (1964).

Professor Mahalanobis made significant contributions to flood control research. In 1922, a disastrous flood occurred in North Bengal.

Another severe flood occurred in Orissa in 1926.

Mahalanobis’ research pointed out the faulty methods of flood-control used by a government-appointed committee, and his recommendations led to a correct path of action in flood-control measures. His recommendations included flushing and irrigation schemes in river systems in Bengal. His research notes submitted to the government of Bengal in 1937 June 2017

was

founded as a

meeting platform for O.R. academicians

and practitioners.

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ORSI Turns 60

India

demonstrated Professor Mahalanobis’ extensive use of quantitative analysis, a technique that was instrumental in the discipline of operational research that emerged following World War II. Professor Mahalanobis died in 1972.

is probably the first country

outside of the Western World to have

authors who

received both the Lanchester Prize

and the Edelman Award

from INFORMS.

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ORSI Activities and Achievements ORSI pursues its objective of promoting operations research through its various activities. These activities can be broadly classified into the following three categories: 1. Publication of journal. Since 1964, ORSI has continuously published the quarterly journal OPSEARCH. Published (print as well as e-version) and distributed by Springer India, it was the first O.R journal from a developing country.The journal has had many eminent O.R. scientists as its editor in chief and is highly acclaimed by O.R. enthusiasts in India and abroad.The International Abstracts in Operations Research (IAOR), which is monitored by IFORS, publishes abstracts of articles from OPSEARCH. 2. Educational course. The scope of formal education in O.R. was limited in India during the early 1960s.

Keeping up with its objective of promoting O.R. education, ORSI introduced a course in O.R. in 1973.The two-year graduate diploma course in O.R. is administered in distance-learning mode, particularly to facilitate O.R. practitioners who are otherwise unable to enroll in any full-time course due to time constraints.The course is duly recognized by the government of India and holds an examination every year in May. 3. Organizing workshops, seminars and conferences. ORSI holds annual conventions for O.R. researchers and practitioners in academics and industry to exchange knowledge on the latest developments in O.R. and allied fields. Participants (both individual and institutional) from India and abroad take part in these conventions that have a different theme every year. The different chapters of ORSI also host and organize workshops, seminars and/or conferences on O.R. topics at regular intervals.

Some notable achievements of ORSI: • ORSI along with IFORS organized the International Conference on Transportation in 1980 in New Delhi.The proceedings were published by North-Holland.

• ORSI and ORS of Britain lent their names to the First International Conference on Operational Research for Development (ICORD - I), which was held at the Indian Institute of Management in Ahmedabad, India, in 1992. Participants from 20 countries attended the event. Professor A.Tripathy from IIMA and Professor Jonathan Rosenhead from the London School of Economics took the initiative for the conference.The conference June 2017

witnessed a position paper named “Ahmedabad Declaration,” which formed the basis for various initiatives of IFORS in O.R. for development.

• ORSI organized the Sixth International Conference of APORS under IFORS (APORS 2003) in 2003 in New Delhi.The conference was titled “Operational Research: Emerging paradigms for Information Technology.

• ORSI hosted the Fifth International Conference on Operational Research for Development in 2005 at Jamshedpur, India.

• ORSI hosted the Eighth International Conference of the Association of Asia-Pacific Operational Research Societies within IFORS (APORS 2009) in 2009 at Jaipur, India.

O.R. Practice in India Operational research has been practiced in India for quite some time in several industries. India is probably the first country outside of the Western World to have authors who received both the Lanchester Prize and the Edelman Award from INFORMS. Most of the airlines and major hotels in India are using dynamic pricing and revenue management systems.The concept is gaining attention in several other sectors, and new academic courses are popping up to promote this field of knowledge. Besides airlines and hotels, other examples of O.R. practice in India include: • Railways: Indian railways are using dynamic pricing with some of its important trains.

• One of the major steelmakers uses an optimization expert system to monitor the quality of blast furnace hot metals.

• Many of the banks and FMCG companies use O.R.-based tools for competitive advantages.

• Routing of vehicles for midday meal scheme in schools [3].

Some significant O.R. practitioners from India include: • Dr. Jagjit Singh, the second president of ORSI, was a leader in the introduction of O.R. in Indian Railways.

• Dr.Vijay Chandru, an academic entrepreneur and INFORMS fellow, is the CEO of a company that deals with data mining, predictive modeling, computational chemistry software engineering, bioinformatics and human genome.

• Professor G. Raghuram, a former president of ORSI, promoted the need for O.R. practice in logistics and supply chain management. He also developed O.R.-based strategies for managing people at the religious site Tirumala, which attracts a huge crowd of pilgrims every day. ormstoday.informs.org

• For the past 15 years, Dr. N. Ravichandran has been conducting many workshops and seminar discussing the practice and promotion of O.R. Future of ORSI The future of O.R. in India is very bright. More than 50,000 people are working in an analytics-related area. Many multinational companies such as IBM, GE, HP and Motorola are present in India and are using or developing analytics tools for competitive advantage. The rapidly expanding interest in O.R. creates the opportunity for ORSI to expand its operations and presence even faster. ORSI can fulfill its objectives even sooner by establishing a meeting ground for O.R. professionals from different industries and helping out in the advancement of knowledge. Some emerging applications of, and opportunities for, O.R. in India include: • Marketing companies requiring help in optimization of marketing efforts.

• Dynamic pricing of electricity at retail electricity market levels.

• The use of analytics in pricing.

• Supply chain analytics for routing, spacing and distribution will require the help of analytics in terms of optimization and simulation.

ORSI is steadily increasing in size and is looking forward for participation from more and more O.R. practitioners, academicians and other enthusiasts.As the future of O.R. in India is very promising, ORSI needs to take a leading role in promoting analytics. ORMS Krishnendra Mitra is a Ph.D. student at the University of Calcutta. Goutam Dutta is a faculty member of IIM, Ahmedabad. He is the president-elect of ORSI and a member of INFORMS.

REFERENCES 1. G. Dutta and A. Tripathy, 1998, “OR in India-Country of Contrasts,” OR/MS Today, Vol. 25, No. 1 (February).

2. B. Mahadevan, S. Sivakumar, D. Dinesh Kumar and K. Ganeshram, “Redesigning Midday Meal Logistics for the Akshaya Patra Foundation: OR at Work in Feeding Hungry School Children,” Interfaces, Vol. 43, No. 6, pp. 530-545.

3. J. O’Connor and E. Robertson, Mahalanobis biography. Available at: http://www-groups.dcs. st-and.ac.uk/history/Biographies/Mahalanobis.html.

4. Orsi.in, 2017, AFOR-2017. Available at: http://orsi.in/afor2017/pastpresident.html.

5. Orsi.in, 2017, AFOR-2017. Available at: http://orsi.in/afor2017/about_orsi.html.

6. Orsi.in, 2017, Operational Research Society of India. Available at: http://www.orsi.in/index.php.

7. Orsidurgapur.in., 2017, Operational Research Society of India, Durgapur Chapter. Available at: http://orsidurgapur.in/synopsis.php.

8. A. Rudra, 1996, “Prasanta Chandra Mahalanobis: a biography,” Oxford University Press, USA. 9. Sinha, B.K., 2010, “Operational Research Society of India,” Wiley Encyclopedia of Operations Research and Management Science. Available at: http://onlinelibrary.wiley.com/ doi/10.1002/9780470400531.eorms0587/full.

Text Analysis

CHEP, a leader in supply chain solutions, saw the INFORMS’ Essential Practice Skills for High-Impact Analytics Projects workshop as an opportunity to improve on the solutions they provide to their clients.

— Ben Eugrin, Director, Supply Chain Solutions for CHEP North America.

“

“

This course provided our team with tools and methodologies based on best practices from various top-tier consulting firms. When paired with our technical supply chain capabilities and experience, these tools allow us to help our client’s structure and solve their most challenging supply chain issues

Video Analytics

Give Them the Essential Skills They Need to Make an Even Bigger Impact

INFORMS offers on-site delivery of our focused, two-day workshop saving your company time and expense. From course customization to follow-up training sessions, INFORMS can tailor the workshop to help your team turn analytical insights into actions that drive innovation, growth, and efficiency.

FOR MORE INFORMATION CONTACT: Bill Griffin, Continuing Education Program Manager, bgriffin@informs.org

Factor Analysis

YOU COUNT ON YOUR ANALYTICS TEAM TO USE THE RIGHT TOOLS FOR THE JOB

Visual Analytics Scenario Analysis Business Experiments

Correlation Analysis

Linear Programming

Sentiment Analysis

Data Mining Image Analytics

Regression Analysis

Monte Carlo Simulation June 2017

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2017 INFORMS ANNUAL MEETING OCTOBER 22â&#x20AC;&#x201C;25 | HOUSTON, TEXAS

Join us in Houston, the healthcare and energy center of the U.S., as well as home to the hub of human spaceflight, for a unique opportunity to connect and network with nearly 6,000 of your colleagues who compose the INFORMS community. Meet new people and listen to intriguing plenary presentations; panel discussions; tutorials; and some of the 100s of oral and poster tracks.

INFORMS is looking forward to hosting the 2017 INFORMS Annual Meeting at the George R. Brown Convention Center where analytics and O.R. professionals from around the world will gather to share research and out of this world ideas.

RESERVE YOUR HOTEL ROOM EARLY WHILE SPACE AVAILABLE. http://meetings2.informs.org/wordpress/houston2017/hotel/

IMPORTANT DATES August 1 - Poster Competition Submission Deadline September 1 - Poster Submission Deadline September 1 - All Presenters Must Register September 21 - Hotel Cut-Off Deadline September 29 - Early Registration Deadline

REGISTER TODAY http://meetings.informs.org/houston2017

IMPORTANT NOTICE:

Presenters not registered

by September 1 will be removed from the conference program.

http://meetings.informs.org/nashville2016

ormstoday.informs.org

news

Inside News

Houston, we solve problems

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Spring Roundtable Roundup

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Preview: Healthcare Conference

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USAF garners UPS Prize

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Student Team Competition

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Turner Broadcasting wins IAAA

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Photos: Scenes from Las Vegas

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Wagner Prize Recipients

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People

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Meetings

Winter Simulation Conference

The 2017 INFORMS Annual Meeting will light up Houston in October.

Source: Thinkstock

2017 INFORMS Annual Meeting prepares for launch in ‘Space City’ The 2017 INFORMS Annual Meeting will be held in Houston, Texas, on Oct. 22-25.

Houston is world renowned for its economy based in aeronautics, energy, manufacturing and transportation. Houston’s energy industry is recognized worldwide for its renewable energy sources, including wind and solar power. Houston is the most diverse city in Texas and has a large and growing international community. Because it is the home of the NASA Lyndon B. Johnson Space Center and its strong ties to the aeronautic industry, it has earned the nickname “Space City.” With a little of something for everyone, Houston lends itself as the perfect location for the next INFORMS Annual Meeting.

The meeting will take place at the George R. Brown Convention Center and the Hilton Americas, with all technical sessions taking place at the Convention Center. INFORMS also has group rates at the Marriott Marquis Houston and the

DoubleTree by Hilton Houston Downtown.

Only a limited number of rooms are blocked and they will sell out quick, so please make your reservations as soon as possible.

Pre-Conference Workshops This year INFORMS is introducing a new pre-conference workshop in conjunction with the Annual Meeting. The Academic Leadership Workshop will take place on June 21, the day before the start of the Annual Meeting. The all-day event is designed for faculty of all ranks with an interest in every level of academic leadership. The workshop provides information that can be useful for becoming efficient and effective leaders.

Panel speakers are highly visible world-class current and former academic administrators.

Participants will have an opportunity to ask questions and network with peers in academic leadership positions. All participants must be nominated by a department head/ chair or college dean.

The 2017 Winter Simulation Conference (WSC 2016) will be held Dec. 3-6 in Las Vegas at the Red Rock Resort.

WSC is celebrating 50 years. In addition to a technical program of unsurpassed scope and quality, WSC is the central meeting place for simulation practitioners, researchers and vendors working in all disciplines in industry, service, government, military and academic sectors.

Submissions are still being accepted for case studies, poster sessions, Ph.D. Colloquium and the vendor track. Complete paper deadlines and requirements are available at www. wintersim.org.

WSC 2017 is sponsored by ACM/ SIGSIM, IISE (Institute of Industrial and Systems Engineers), INFORMSSIM and SCS (Society for Modeling and Simulation International), with technical co-sponsorship from ASA (American Statistical Association), ASIM (Arbeitsgemeinschaft Simulation), IEEE/ SMC (Systems, Man and Cybernetics) and NIST (National Institute of Standards and Technology).

For more information, visit the WSC website: http://meetings2.informs.org/ wordpress/wsc2017/ ORMS

Annual Meeting, continued on p. 40

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new s Annual Meeting, continued from p. 39

Another pre-conference workshop that is being introduced this year is the INFORMS Workshop on Data Science. Sponsored by the INFORMS College on Artificial Intelligence, this workshop is a premier research event dedicated to developing novel data science theories, algorithms and methods to solve challenging and practical problems that benefit business and society at large. The conference invites innovative data science research contributions that address business and societal challenges from the lens of statistical learning, data mining, machine learning and artificial intelligence. Contributions on novel methods may be motivated by insightful observations on the shortcomings of stateof-the art data science methods in addressing practical challenges, or may propose entirely novel data science problems. Research contributions on theoretical and methodological foundations of data science, such as optimization for machine learning and new algorithms for data mining, are also welcome.

Networking Along with the abundance of educational opportunities, the conference will offer several opportunities for connecting and networking. The Welcome Reception will be held on Oct. 22. Subdivision meetings will be held predominantly on October 23 in the evening. On Oct. 24, INFORMS will host the General Reception at Minute Maid Park, Home of the Houston Astros.

Another unique networking opportunity for student members is the Coffee with a Member program. This wonderful program connects INFORMS students with some of INFORMS most enthusiastic members for 15-minute impromptu meetings and some sage INFORMS advice. We know the Annual Meeting can be a bit overwhelming and hope these casual meetings will make students more comfortable, knowledgeable and enthusiastic about both the meeting and INFORMS. Space is limited and open to firsttime attendees/participants only. Students may enroll for this program when they register for the meeting.

Career Center A huge benefit of the INFORMS Annual Meeting for employers and job seekers is the INFORMS Career Center. The Career Center and activities provide employers 40 | ORMS Today

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with the opportunity to meet and collect resumes from numerous job seekers in a short period of time, early in the meeting, and to schedule and set-up private interviews later in the meeting. Career Center activities are free for all individual meeting registrants. Job seekers should register in the INFORMS Career Center so employers will know you are attending. Be sure to post your resume or anonymous career profile that will lead employers to you. Job seekers should review Career Center Resources prior to attending

the job fair to make sure your resume and interviewing skills are in tip-top shape.

We hope you will attend this unique opportunity to connect and network with more than 5,000 INFORMS members, students, prospective employees, and academic and industry experts. We look forward to seeing you in Houston!

For more information on any of the events listed in this article or other activities at the Annual Meeting, visit www.meetings. informs.org/houston2017. ORMS

Spring 2017 Roundtable roundup

By Brian Eck The spring 2017 Roundtable Meeting was held on April 1-2 at Caesars Palace in Las Vegas. The meeting theme was “Roundtable Companies” and featured five talks by member organizations.

Roundtable breakout session in Las Vegas.

The main program Source: Roundtable began with a presentation by Jeff Arbogast from Air Liquide. The described the work of the Strategic company has special relevance to Las Vegas Planning and Modeling (SPaM) team of for its early work in neon lights. Jeff works in analysts in HP, and some recent high impact computational and data science R&D, and he wins in affecting working capital. shared his experiences in real-time optimizaThe final speaker was Brian Eck from tion of pipelines, vendor-managed inventory, Google. Brian highlighted ways in which and alarm detection and management, in- Google culture and context provide fertile cluding extensive collaboration with partner ground for advanced analytics. He described universities. examples of how analysts are organized, as The group then heard from Stefan Karisch, well as specific projects within Google, from director of analytics at Boeing. He described capacity planning at GFiber to task scheduling Boeing’s work with Commercial Aviation for Terra-Bella (earth imaging satellites).

Services (CAS), which is responsible for keeping The meeting included a dynamic and exairlines’ fleets flying safely and efficiently. tensive discussion, in small breakout groups, The third speaker was Jim Williams of “What Does the Roundtable Think?” While from Fair Isaac (FICO). Jim described taking these sessions in the past have focused on a “decisions first” approach (versus data or one or two areas, this time the group conmethods first), which resonated with other sidered several diverse topics, ranging from Roundtable members. He outlined a case perceived value of O.R., to training, to how study on helping an automotive financing O.R. relates to data science to how member company deal with delinquencies in the 2008 company teams measure success. recession, and he wrapped up by sharing Roundtable President-Elect Kathy success factors in hiring analytics talent.

Lange of SAS conducted a business meetThe fourth speaker was Cara Curtland ing with 26 member representatives, six from HP Inc., a $48 billion business in alternate member representatives and two personal systems and printing. Cara member guests. ORMS ormstoday.informs.org

ormstoday.informs.org

INFORMS Healthcare 2017: Optimizing operations & outcomes

By Edwin Romeijn and Joris van de Klundert Since the first edition in 2011, the biennial INFORMS Healthcare Conference has quickly developed into the global leading conference in its field. This is further underlined by the decision of the INFORMS Health Applications Society to cross the ocean for the fourth edition, which will be held in Rotterdam, Netherlands, on July 26-28.

The Netherlands is widely renowned for its world-class health system that has topped the European Consumer Health Index since 2008. While Rotterdam may be best known for being the world’s largest port for more than four decades (1962-2004), it is presently developing into a modern health and life sciences hot spot. It is already home to an internationally oriented health and life sciences community of almost 70,000 people and 4,000 companies. According to Lonely Planet, “this metropolitan jewel of the Netherlands is riding a wave of urban development, redevelopment and regeneration.”

The largest academic hospital in the Netherlands, Erasmus Medical Center, and Erasmus University are also located in Rotterdam.

As a global logistics hub and health and life sciences hot spot, Rotterdam forms a perfect location for the INFORMS Healthcare 2017 conference focused on “optimizing operations & outcomes.” The conference offers a platform for the INFORMS community to make the next step on the path of optimizing health through advancing theory and practice of operations research, management science and analytics. The conference will offer a wide selection of contributions from the United States and Europe (in particular, the Netherlands), as well from developing countries where outcome improvements are needed most. To this purpose, the conference covers areas such as disease and treatment modeling, personalized medicine, medical decision-making, healthcare analytics and machine learning, health information technology and management, health operations management, health and humanitarian systems, disparities in health and global health, and public health and policy-making.

The Markthal (Market Hall) is an example of Rotterdam’s fine architecture.

Source: Rotterdam.Branding. Photographer: Ossip van Duivenbode.

The program will include plenary lectures from leading scientists in the field, including Dimitris Bertsimas of MIT and INFORMS president Brian Denton of the University of Michigan. Other plenary lectures will be delivered by health system leaders such as Dr. Eric de Roodenbeke, president of the International Hospital Federation, who will present his view on how information technology is driving the transformation of hospitals. In addition, Secretary General Erik Gerritsen of the Dutch Ministry of Health, Welfare & Sports will address the Dutch view on health system advancement, with a special emphasis on the role of information technology and big data. On behalf of the European Commission, Gisele Roesems-Kerremans of the Department for eHealth, Well Being and Aging, will outline European policies and research priorities.

Of course, the conference is primarily a place for the many participants to meet, present and discuss their work. In addition to the poster presentations, there will be more than 100 sessions and 400 talks. Discussions may continue in the open spaces of the downtown conference center De Doelen, the terraces of Rotterdam during

lunch, dinner or nightlife, or at the conference reception on a historic paddle-wheel steamer cruising the Port of Rotterdam.

On the day before the conference starts, the conference offers organized visits to Dutch healthcare best practices. For example, it offers site visits to: the newly designed Erasmus Medical Center, the leanest hospital in The Netherlands; Reinier de Graaff Gasthuis in Delft; and the Dutch Healthcare Quality Institute, the hub of the Dutch health data network. For the day after the conference, conference attendees can take advantage of organized sightseeing tours to nearby sites (UNESCO world heritage Kinderdijk, the Delta works) or cities (Amsterdam, Gouda), before some may catch a plane, train or boat to Bath (United Kingdom), where the EURO Working Group on Operational Research Applied to Health Services (ORAHS) will hold its annual meeting starting July 30. This is yet another good reason to join us in optimizing operations and outcomes from July 26-28 in Rotterdam.

We look forward to seeing you! ORMS Edwin Romeijn is the program chair and Joris van de Klundert is the conference chair of INFORMS Healthcare 2017.

June 2017

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new s Air Force Academy’s O.R. program saluted The U.S. Air Force Academy won the 2017 UPS George D. Smith Prize for its operations research (O.R.) program, which prepares graduates to become frontline O.R. practitioners as analysts in the Air Force. The program exposes more than 50 percent of cadets to at least one O.R. course and provides cadets the opportunity to graduate with a Bachelor of Science degree in O.R. A year-long applied senior capstone serves as the apex of the program, during which teams of cadets consult for military, corporate, local government and nonprofit organizations to address real-world problems.

Organizations that have teamed with the USAF program in the past include DARPA, the Missile Defense Agency, Lockheed Martin, Walmart and the Healing Warriors Program.

Named in honor of the late UPS Chief Executive Officer – a champion of operations researchers at a leading Fortune 500 corporation – the UPS George D. Smith Prize is created in the spirit of strengthening

ties between industry and the schools of higher education that graduate young practitioners of operations research. The prize is awarded to an academic department or program for effective and innovative preparation of students to be good practitioners of operations research or analytics.

“By teaming with a Jack Levis of UPS (far left) and Prize Committee Chair Robin variety of organizations Lougee (far right) congratulate the USAF Academy. to provide its students access to real-world data and problemrise, it is more important than ever for young solving opportunities, the Air Force Academy professionals to stand out as the top talent. stands out among other academic institutions The Air Force Academy’s program makes in its dedication to preparing graduates for sure they do.” success,” said Melissa Moore, executive The award was presented at the 2017 director of INFORMS. “As the demand for INFORMS Conference on Business Analytics & O.R. and analytics professionals continues to Operations Research. ORMS

Student Team Competition targets food production With the backdrop of a fast-growing global population and looming challenges to produce enough food to feed the world, a group of students from the University of Warwick, Nottingham University and Cardiff University in the United Kingdom developed a new method to produce better-performing soybean strains that could lead to a worldwide increase in food production. Their solution was developed as part of the first annual O.R. and Analytics Student Team Competition. The new competition, organized

by INFORMS and sponsored this year by Syngenta, challenges students to apply their considerable talent to develop solutions to some of the biggest challenges facing our world today.

Eight teams comprised of graduate and undergraduate O.R. and analytics students from around the world competed in this year’s inaugural completion. Each team used the same data sets and software options to develop solutions to provide unique new analysis of data on soybean varieties bred for commercialization, and propose solutions for developing better performing plants.

“The O.R. and Analytics Student Team Competition not only shines a spotlight on the incredible young talent that is preparing to enter the field of O.R. and analytics, but provides these student teams the opportunity to hone the skill sets that will place them on the path to success as they embark on their careers,” said Melissa Moore, executive director of INFORMS. “From prob-

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lem-solving and teamwork, to documenting and communicating their findings, the competition prepares students for the demands of a real-world workplace experience.”

“We are honored to have won the first O.R. and Analytics Student Team Competition,” said Peter Riley, student team leader.

(L-r): Aurelie Thiele presents the U.K.-based team of Peter “Not only did we have the Riley, Anna Scholes and Adam Green as the winner of the O.R. chance to test our skills and Analytics Student Team Competition. against brilliant students from around the world, “Syngenta is proud to support innovative but we were able to do so in way that could help thinking among emerging young leaders in make a lasting difference for countless people. It analytics,” said Joseph Byrum, senior R&D makes for a truly rewarding and fulfilling experistrategic marketing executive with Syngenta ence, and we look forward to building on what and Syngenta lead for the Student Competition we’ve learned and accomplished as we move organizing committee. “This competition served forward in our studies and careers.” as an excellent entry point for students interested The winning team was announced at the in learning more about how analytics can help 2017 INFORMS Business Analytics Conference solve the challenges facing agriculture today.” in Las Vegas, following a final oral presentation Other finalists in the 2017 competition by each finalist team. Finalists were selected by included: Drexel University, National University a panel of industry and academic experts based of Singapore, Özyegn University (Turkey), on each teams’ use of the full analytics process, Université catholique de Louvain Team 1 from framing the problem to methodology (Belgium), Université catholique de Louvain Team selection, data use, model building, and 2 (Belgium), University of Cincinnati and University quantitative analysis. of North Carolina at Chapel Hill. ORMS ormstoday.informs.org

ormstoday.informs.org

Turner Broadcasting receives Innovative Applications in Analytics Award

By Scott Grasman Turner Broadcasting System, Inc. received the 2017 Innovative Applications in Analytics Award at the 2017 INFORMS Analytics Conference in Las Vegas. The winning entry, “Audience Targeting Solutions Powered by Advanced Analytics,” was presented by Wes Chaar, José Antonio Carbajal and Peter Williams from Turner Broadcasting.

The Innovative Applications in Analytics Award (IAAA), sponsored by Caterpillar and the INFORMS Analytics Society, recognizes creative and unique application of analytical techniques. The prize “promotes the awareness and value of the creative combination of analytics techniques in unusual applications to provide insights and business value.” To win the award, implementations must integrate theoretical advances and innovative applications in order to create value.

Finalists presented their work at the conference to a judging committee chaired

by Scott Grasman from Rochester Institute of Technology.

For decades, television advertisement deals had been guaranteed using only primary demographic metrics specified by age and gender. In the last few years, data fusion has allowed viewership data to be fused with frequent shopper card data, credit card data or even custom surveys to construct targeted TV audience segments such as “cereal buyers” or “auto intenders.” These new, more granular audience segments have challenged traditional ways of forecasting, scheduling, and managing inventory in the media industry.

Through advanced analytics, Turner has taken the lead in offering targeted ad products that better address the needs of our advertiser and agency partners.

Turner has developed two core audience targeting solutions: TargetingNOW and AudienceNOW. TargetingNOW takes an existing advertising deal, which is still guaranteed on demographic viewership and maintains its original media mix, and optimizes its spot placements to increase the delivery of a secondary targeted seg-

ment. AudienceNOW relaxes many, but not all, of the traditional mix constraints to produce fully optimized deals and spot placements that maximize targeted audience delivery across the entire portfolio of Turner’s networks.

A suite of advanced analytics tools power these targeting solutions. On the descriptive side, analysis and visualization tools present detailed historical or predictive information for particular segments and allow comparison of Turner networks against competitors. On the predictive side, a scalable, accurate and data-agnostic forecasting approach called Competitive Audience Estimation can build granular estimates for virtually any audience segment.

Finally, on the prescriptive side, large-scale, mixed-integer-programming models optimize deal composition and spot placements.

Second prize was awarded to Valentina Ferretti from London School of Economics and Political Science for her work on “How to Regenerate Disused Railways? An Integrated Analytics Approach.”

Inactive railway lines and disused station buildings constitute an increasingly important heritage asset and are becoming the focus of regeneration processes worldwide. However, the decision of what to do in order to reuse abandoned railways represents a complex decision-making problem, involving heterogeneous impacts and multiple stakeholders leading to conflicting objectives. Such a context calls for the use of analytics able to support transparent, replicable and justifiable processes/results.

This project proposes a combination of different analytics to effectively support collaborative decision-making processes where a decision must be made among competing options. The study developed and tested an integrated analytical approach by combining: • preference elicitation analytics with visualization analytics in the descriptive phase of the process;

• sensitivity analysis with visualization analytics in the predictive phase of the process; and • prescriptive decision analysis with facilitated modelling throughout the whole process.

The proposed framework has been tested on a real case study dealing with transportation systems’ planning in Northern Italy, where several passenger railway lines have recently been abandoned and replaced by bus services.

The main objective of the study was to investigate which role integrated decision analytics can play to support heterogeneous impacts’ aggregation in territorial planning, by discussing the operability, applicability and transparency of the developed methodological framework.

The contribution brought by the study is twofold and refers to: (i) improved operability of the proposed tools obtained by combining visualization analytics with consolidated preference elicitation protocols for assessing multiple impacts and (ii) the provision of a replicable working tool for policy-makers.

2018 Award Submissions Implementations that span applications of descriptive, predictive or prescriptive analytics, as well as data creation, collection and dissemination that support or enable novel analytical methods, can be submitted for the 2018 Innovative Applications in Analytics Award. Applicants must submit a 500-1,000-word summary by Sept. 1 to Committee Chair Juan R. Jaramillo (jaramijr@farmingdale.edu). Semifinalists will be notified by Sept. 30, and finalists will be notified by Dec. 9. Finalist presentations will take place at the INFORMS Analytics Conference in Baltimore, April 15-17, 2018.

The winner will present at the INFORMS Annual Meeting in Phoenix, Nov. 4-7, 2018. For more details, contact the committee chair. ORMS June 2017

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Viva Las Vegas 2017: Scenes from the INFORMS Business Analytics & O.R. Conference

Clockwise, from right: Las Vegas sparkled and so did the conference; talking shop with the exhibitors; Edelman Award finalists take center stage; job fair participants and employers make their pitch; happy conference campers ready for a big day; INFORMS President Brian Denton welcomes attendees.

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Clockwise, from above: UPS Prize Committee members have their eyes on the prize winner; young attendees enjoy the scene; the INFORMS booth was stacked with information; poster sessions offered a showcase for many projects; Peter Bell and INFORMS Executive Director Melissa Moore; large crowds were the norm; the table was set for the Edelman Gala; Caesars Palace was quite a sight â&#x20AC;Ś and what a site; the lineup of plenary speakers was outstanding.

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new s Swedish team wins Wagner Prize for unique truck-routing solution Every day millions of people rely on GPS to navigate to and from locations around the world. But what happens if you must frequently travel through an area that is accessed primarily by private roads, or you drive a vehicle that cannot safely navigate on certain routes? For their work in identifying a solution to this problem, Mikael Rönnqvist of the Université Laval, Canada; Gert Andersson, Gunnar Svenson and Patrik Flisberg of the Forestry Research Institute of Sweden; and Lars-Erik Jönsson of the SDC, Sundsvall, Sweden, were presented the 2016 Daniel H. Wagner Prize for Excellence in Operations Research Practice by INFORMS. The prize, first announced at the 2016 INFORMS Annual Meeting, was formally presented as part of this year’s Edelman Gala in Las Vegas. Allen Butler, president of Wagner & Associates and chair of the award committee, made the presentation.

The prize-winning paper, “Calibrated Route Finder – Social, Safe, Environmental and Cost-Effective Truck Routing,” was recognized not only for its success in real-world application, but for a strong mathematical foundation that was clearly and concisely communicated in both the writing and presentation.

The research was based on the need for drivers of heavy trucks, particularly those working in the forestry industry, to have a route finder that goes beyond the typical GPS tool parameters of shortest and/or fastest route. In Sweden, where nearly two-thirds of the roads are private, a percentage that is even higher than in forested areas, GPS tools are limited by the lack of publicly available data for these private roads. As a result, GPS tools may suggest routes that are ill-suited for trucks, leading to high fuel consumption, long driving hours and driving on dangerous roads, or the GPS tool may be unable to find any route at all.

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that collects and analyzes a broader range of data to better identify optimal driving routes for drivers of heavy trucks in Sweden.

The other finalists for the 2016 award included: • “Vungle Inc. Improves Monetization Using Data Analytics” by Ioannis Fragkos, Erasmus University, Netherlands; Bert De Reyck, University College Allen Butler (middle), president of Wagner & Associates and London; Yael S. Grushchair of the Wagner Prize Committee, congratulates Mikael ka-Cockayne, Casey Rönnqvist (left) and Gunnar Svenson (right).

Lichtendahl, University of Virginia; Hammond • “IBM Cognitive Technology Helps Guerin, Vungle Inc. Aqualia Reduce Costs and Save Re• “Data-Driven Optimization For sources in Wastewater Treatment” by Multi-disciplinary Staffing in Mayo Alexander Zadorojniy, Segev WasserClinic Improves Patient Experience” by krug, Sergey Zeltyn, Vladimir Lipets, Mustafa Sir, David Nestler, Thomas IBM Research, Haifa Hellmich, Devashish Das, Michael J. Laughlin, Michon Dohlman, Kalyan Sponsored by the INFORMS Section Pasupathy, Mayo Clinic on Practice, the Wagner Prize emphasizes • “Optimizing New Vehicle Inventory the quality and coherence of the analysis at General Motors” by Robert Inman, used in practice. Dr. Daniel H. Wagner Michael Frick, Thomas Hitchman, strove for strong mathematics applied to Robert Muiter, Jonathan Owen, Gerpractical problems, supported by clear ald Takasaki, General Motors and intelligible writing. The Wagner Prize • “Implementation of the Genetic Gain recognizes those principles by emphasizing Performance Metric Accelerates good writing, strong analytical content and Agricultural Productivity” by Joseph verifiable practice successes. Past awardees Byrum, Craig Davis, Greg Doonan, include practitioners and researchers from Tracy Doubler, Syngenta; Bill Beavis, CDC, Ford, U.S. Coast Guard, Intel, IBM Iowa State University; Von Kaster, Sam T. J. Watson Research, Schneider National, Parry, Ronald Mowers, Arizona State Boston University, University of Florida and University others. ORMS

H T T P : / / W W W. A N A LY T I C S - M A G A Z I N E . O R G

DRIVING BETTER BUSINESS DECISIONS

M AY/ J UN E 2017

Check out the May/June 2017 Issue of Analytics Now Available at: www.analytics-magazine.org ormstoday.informs.org

ormstoday.informs.org

People H u i Ya n g a n d Eva K. Lee are the coeditors of a new book that focuses on statistical and operational research methods and tools that are being used to improve the healthcare industry. Published by Hui Yang Wiley, “Healthcare Analytics: From Data to Knowledge to Healthcare Improvement” provides an integrated and comprehensive look at recent research advancements in datadriven healthcare analytics Eva K. Lee in an effort to provide more personalized and smarter healthcare services.

The book features contributions from leading researchers from around the world who shed light on new approaches within the realm of healthcare analytics. The text features discussions on contemporary methods and techniques to address the handling of rich and largescale healthcare data, as well as the

overall optimization of healthcare system operations. Real-world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry are also presented.

“Healthcare Analytics” is a reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems and economics. It is also useful for graduate students studying operations research, industrial engineering, business and public health departments.

Yang is the Harold and Inge Marcus Career Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering in the College of Engineering at Penn State University. Lee is a professor in the H. Milton Stewart School of Industrial and Systems Engineering and director of the Center for Operations Research in Medicine and Health Care at Georgia Tech.

She is also a distinguished scholar at both the Emory University School of Medicine and Georgia Tech. ORMS

Tom Willemain, a software entrepreneur, statistics professor and well-known figure in the operations research community, volunteered for a year-long sabbatical tour of duty in the National Security Agency Tom Willemain (NSA). He recounts his experience in the recently released book, “Working on the Dark Side of the Moon: Life inside the National Security Agency,” in which he provides the first ground-level look inside the super-secret NSA and a shadowy think tank affiliated with it.

Willemain ended up spending several years moving between the business and academic worlds and the secret world. The book records his impressions of people and places never before described in such intimate detail.

A deeply personal account of the years spent within the most secretive organization in the world, the book explores the range of emotions an outsider experiences while crossing over to the “inside.” It also shows the positive side of an agency whose secrecy hides dedicated men and women devoted to protecting the country while honoring the Constitution.

Dr. Willemain served as an expert statistical consultant to the NSA at Fort Meade, Md., and as a member of the adjunct research staff at an affiliated think tank, the Institute for Defense Analyses Center for Computing Sciences (IDA/ CCS). He is professor emeritus of Industrial and Systems Engineering at Rensselaer Polytechnic Institute, having previously held faculty positions at Harvard’s Kennedy School of Government and the Massachusetts Institute of Technology.

Fo r m o r e i n f o r m a t i o n , e m a i l : To m W @ S m a r t C o r p . c o m o r v i s i t TomWillemain.com. ORMS

Meetings INFORMS Annual & International Meetings July 26-28, 2017 INFORMS 2017 Healthcare Conference

De Doelen International Congress Centre Rotterdam, the Netherlands Chair: Joris van de Klundert, Erasmus University Rotterdam http://meetings.informs.org/healthcare2017/

Oct. 22-25, 2017 INFORMS Annual Meeting

George R. Brown Convention Center & Hilton Americas, Houston Chair: William Klimack, Chevron http://meetings.informs.org/houston2017/

2018 April 15-17, 2018 INFORMS Conference on Business Analytics & Operations Research Marriott Waterfront Hotel, Baltimore Chair: Jack Kloeber, Kromite, LLC http://meetings.informs.org/analytics2018/

Nov. 4-7, 2018 INFORMS Annual Meeting

Phoenix Convention Center & Sheraton Phoenix Hotel, Phoenix Chair: Young-Jun Son, University of Arizona

INFORMS Community Meetings June 26-27, 2017 INFORMS Advances in Decision Analysis The University of Texas at Austin Austin, Texas Chair: Casey Lichtendahl, University of Virginia http://connect.informs.org/das/conferences

June 29-30, 2017 INFORMS Revenue Management & Pricing Section Conference

Centrum Wiskunde & Informatica (CWI) Amsterdam Chair: Arnoud Den Boer http://connect.informs.org/rmp/conferences/rmp-conferences

July 10-12, 2017 INFORMS 19th Applied Probability Conference

Northwestern University Evanston, Ill. Chair: Achal Bassanboo http://www.kellogg.northwestern.edu/departments/operations/ events/informs.aspx

July 27-29, 2017 INFORMS Transportation Science and Logistics Conference

Loyola University Chicago Chicago Chair: Pitu Mirchandani, Arizona State University http://connect.informs.org/tsl/conferences/tsl-conference

Go to www.informs.org/Conf for a searchable INFORMS Conference Calendar.

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LINEAR PROGRAMMING SOFTWARE SURVEY

Fourteenth in a series of LP surveys focuses on characteristics that are valuable in choosing products.

Image © Wavebreak Media Ltd. | 123rf.com

By Robert Fourer

Linear Programming This is the fourteenth in a series of surveys of software for linear programming, dating back to 1990. As in the case of earlier surveys, information has been gathered by means of a questionnaire sent to software vendors

by OR/MS Today. Results are summarized by product in the tables following this article. Further information is available directly from the vendors, for whom contact information is provided in the directory on page 50.

For this year’s survey, the questionnaire was revised to focus somewhat less on technical distinctions and more on characteristics that are valuable in choosing products to investigate further. The ordering of topics below is roughly parallel to the organization of the tables, and terms in bold correspond to table headings.

The printed table is limited to responses available by press time, but additional responses are welcome and will be added to the online version of the survey listing. To learn more, write to Online Projects Manager Patton McGinley, patton@lionhrtpub.com, or go directly to the survey at www. lionhrtpub.com/ancill/lpsurvey2017.shtml.

Products Covered Products listed in this survey are concerned, at the least, with minimizing or maximizing linear constraints subject to linear 48 | ORMS Today

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equalities and inequalities in numerical decision variables.All products provide for continuous variables that may take any values between their bounds, and many also accommodate integer variables that are limited to whole-number values in some way.The respectively continuous and discrete problems that use these variables are commonly distinguished as linear programs (LPs) and integer or mixed-integer linear programs (IPs/ILPs or MIPs/MILPs), but for convenience “LP software” is used herein as a general term for the packages covered, and “LP” refers to linear problems that may or may not have some integer variables.

Some of the listed products handle discrete variables and constraints of other kinds, quadratic and more general nonlinearities, and even problems outside of optimization.This survey focuses on developments and trends in the linear programming and related integer programming aspects of the software, however. Also, the listing excludes products that address only certain applications or formulations of LP, or that are not targeted to large LP instances, as these products are more properly evaluated in the context of other broad categories of optimization software.

Types of Packages Although the products surveyed have a common purpose and share many aspects of design, they are best understood as incorporating two complementary but fundamentally different types ormstoday.informs.org

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of software. Solver software takes an instance of an LP model as input, applies a combination of algorithmic methods designed to find solutions that are optimal (or reasonably close to optimal), and returns the results. Modeling environments mediate between human modelers and solvers, providing general and intuitive ways to express symbolic models, while offering features for importing data, generating problem instances, invoking solvers, analyzing results, scripting extended algorithmic schemes and interfacing to broader applications. Products of this latter kind are typically built around a computer modeling language either designed specifically for describing optimization models or adapted from the features of an already popular programming language.

Much of the software for linear programming is specialized either to modeling or to solving.Thus, solvers typically link to many modeling systems, and modeling systems link to many solvers. In some cases the two may be acquired as separate products and linked by the purchaser, but more commonly they are available bundled in various ways. Several developers of general-purpose modeling systems arrange to offer a variety of bundled solvers, providing modelers with an easy way to benchmark competing solvers before committing to purchase one. Some solver developers similarly offer bundles with modeling systems, while others focus on integrated systems that provide a modeling environment specifically for their own solvers.

Interfaces to Other Software Since optimization models are usually developed in the context of some larger algorithmic scheme or application (or both), the ability of LP software to be embedded is often a key consideration. Thus, although virtually any of the listed products can be run as an independent application in some kind of stand-alone mode, many are available as callable programs, generally in the form of class libraries in an object-oriented framework. Popular general-purpose programming languages and specialized math/stat languages are supported for this purpose; some products also offer their own specialized application development tools.

Solver systems have long been available as program libraries, allowing them to be embedded within application-specific systems and interfaces. As solver library designs have evolved, some have taken on aspects of symbolic modeling, such as algebraic specification of constraints. At the same time, modeling systems have been extended to offer their own program libraries, so that the considerable advantages of developing and maintaining a model formulation can be carried over into application software that solves instances of a model. It is possible to embed an entire modeling system or a particular model or an instance of a model; not all systems provide all possibilities, so some study is necessary to determine which products are right for a given project in this respect.

Most LP software is available as binaries that are ready to run or to link into the user’s applications. The table also identifies products that make their source code freely available under one of the recognized open source licenses; the largest number of these are affiliated with the COIN-OR project

(www.coin-or.org) and many are maintained in repositories at GitHub (www.github.com). Open source is attractive for situations where budgets are tight or where the greatest degree of flexibility is required – such as when new or customized algorithmic ideas are being investigated. Some study may be necessary however to determine whether a desired combination of efficiency, convenience and support is currently available in open source LP software.

The application development environments provided by spreadsheet and database programs have proved to be particularly useful tools for embedding LP software. At the least, most LP modeling environments can read and write common spreadsheet and database file formats. Some LP products also work as spreadsheet add-ins whose appeal to users and convenience for development are widely appreciated. The solver add-in that comes packaged with Excel is effective for relatively small and easy problems; independent developers offer more powerful and general spreadsheet optimizers.

Virtually all LP solvers accept input of model instances expressed in simple text file formats, especially the “MPS” format dating back many decades and various “LP” formats that resemble textbook examples complete with + and = signs.

These formats mainly serve for submitting bug reports and for communicating benchmark problems. Modeling systems use much more general and efficient formats for communicating problem instances to solvers and for retrieving results, but each has adopted its own format, and efforts at standardization have proceeded only slowly.

Platforms It is by now standard to provide support for all three of the most popular computing platforms: Windows, Linux and macOS. Several other Unix variants appear frequently among Other systems supported (and indeed some LP systems support macOS through its underlying Unix-based shell). Also, there is increasing availability to run directly in a web browser.

Solvers offering parallel versions for shared memory have become common, as the number of cores available in offthe-shelf PCs continues to increase. Indeed, the automatic use of all available cores has become routine for some purposes, particularly the solution of the linear system that is central to interior-point LP methods and the exploration of the search tree that is fundamental to MIP solvers. Support for distributed memory, using multiple independent computers connected by a network, is now quite common though it requires some additional work to set up.

Pricing and Distribution The table shows commercial single licenses running from hundreds to thousands of dollars, but as most vendors have a considerable range of license types and pricing arrangements, it is advisable to get a quote or consult a complete price sheet before arriving at any conclusions about costs. The most popular MIP solvers do tend to be at the high end of the price range.

Special terms are often available for multiple purchases and for Software Survey, continued on p50

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other licenses of varied kinds. Since solver performance varies considerably from problem to problem and from product to product, buyers are well advised to benchmark problems of interest before deciding which products are likely to offer the best value.

All of the listed commercial products offer a variety of free or highly reduced-cost academic offerings for research and educational use. Free options may be limited in problem size (demo versions) or in time of validity (trial versions); some are sufficiently unrestricted to permit long-term use on largescale projects. Open-source packages are, of course, free to use, though a few carry restrictions on inclusion in commercial application software.

Local installations remain the dominant mode of LP software application, but optimization in the cloud or as a software service has become an established alternative. A still-growing roster of modeling systems and solvers is available for testing through the online NEOS Server (www.neosserver.org); as a free service, NEOS does not provide guarantees of confidentiality or performance, but it is appropriate for many projects and has been averaging more than 40,000 requests a month. Commercial cloud availability has also continued to expand, for services provided by vendors such as Amazon as well as services provided by customers on their own computing facilities. Offerings range from simple NEOS-style submissions of individual optimization jobs to sophisticated interfaces managing dynamic server pools.

VENDOR DIRECTORY

AIMMS, Inc. 11711 SE 8th Street Suite 303 Bellevue, WA 98005 425-458-4024 info@aimms.com www.aimms.com

AMPL Optimization Inc. 900 Sierra Place SE Albuquerque, NM 87108-3379 773-336-2675 425-940-6286 info@ampl.com http://ampl.com

Aptech Systems Inc. 2350 East Germann Road, Suite #21 P.O. Box 250 Chandler, AZ 85286 360-886-7100 360-886-8922 info@aptech.com www.aptech.com

Artelys 81 rue Saint Lazare Paris 75009 France 144778900 142962261 info-knitro@artelys.com https://www.artelys.com/knitro

COIN-OR Foundation

Problem Types LP software packages have increasingly been extended to handle more than just linear problems. Piecewise-linear and positive semi-definite quadratic objectives and constraints, in continuous or integer variables, are a common extension; they can be solved by generalizations to LP methods, though not always as easily. Also, many products accept conic quadratic formulations, which are particularly versatile because a variety of non-quadratic and even non-convex function classes admit translations to them, thus extending the range of applications that can be addressed.

The variety of specialized variable types and constraint types continues to increase. As a result, many logical conditions can be stated directly, bypassing challenging or error-prone reformulation in terms of auxiliary variables and constraints.

Sometimes a direct statement of a logical condition permits faster solving as well.

Although this survey is focused on LP, quite a few of the listed products can also handle general convex and even general nonlinear objectives and constraints. The listing should not be considered exhaustive with respect to nonlinear solver packages, however.

Algorithms LP solvers offer a choice of simplex and interior-point methods for continuous problems. MIP solvers incorporate sophisticated branch-and-cut frameworks to accommodate

Fair Isaac Corporation 181 Metro Drive San Jose, CA 95110 408-535-1500 408 535-1776 info@fico.com http://www.fico.com/xpress

Free Software Foundation, Inc. 51 Franklin Street, Fifth Floor Boston, MA 02110-1301 617-542-5942 617-542-2652 info@fsf.org http://www.fsf.org/

Frontline Systems Inc. P.O. Box 4288 Incline Village, NV 89450 775-831-0300 775-831-0314 info@solver.com www.solver.com/analytic-solver & rason. com

GAMS Development Corp.

1217 Potomac Street NW Washington, DC 20007 202-342-0180 202-342-0181 sales@gams.com https://www.gams.com

Gurobi Optimization, Inc. 3733-1 Westheimer Road #1001 Houston, TX 77027 713-871-9341 713-960-0793 info@gurobi.com www.gurobi.com

IBM 1681 route des Dolines Valbonne 6560 France +33 4 92 96 8672 +33 4 92 96 61 62 ferenc.katai@ibm.com https://www.ibm.com/us-en/marketplace/ ibm-ilog-cplex

Julian Hall University of Edinburgh, School of Mathematics James Clerk Maxwell Building, Peter Guthrie Tait Road Edinburgh EH9 3FD UK +44 131 650 5075 jajhall@ed.ac.uk http://www.maths.ed.ac.uk/hall/hsol/

JuliaOpt http://www.juliaopt.org/

Lehigh University ted@lehigh.edu https://github.com/tkralphs/MibS

info@coin-or.org http://www.coin-or.org

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even quite difficult problems, often with help from local search heuristics and specialized problem-simplification routines. Solvers have also been extended with other algorithms of varied kinds, to improve their effectiveness or range of applicability.

Solver performance has steadily improved, from the first ORMS Today survey to the present one – but less from algorithmic breakthroughs than through an accumulation of ideas for reducing problem size, tightening bounds, finding better solutions and taking advantage of common problem structures. Inevitably this has led to very long option lists; close attention to solver documentation can suggest which option settings might improve performance on a particular problem, but often only a fraction of the possibilities can be tested. Thus, an important aspect of any solver is its choice of default settings that adapt to characteristics of the problem at hand; a few solvers also provide automated “tuning” features that can suggest to the user which options to set.

Nevertheless, solver performance remains highly problem-specific. For applications of any difficulty, it is advisable to benchmark several relevant solvers on sample problems of interest, rather than making a quick choice based on measures of average solver performance.

What’s Next?

Vendors’ summaries of new features since the previous survey are the expected mix of new algorithms, faster

LINDO Systems, Inc. 1415 North Dayton Street Chicago, IL 60622 312-988-7422 312-988-9065 info@lindo.com www.lindo.com

LocalSolver 36 avenue Hoche Paris Ile-de-France 75008 France +33 9 72 31 98 43 contact@localsolver.com http://www.localsolver.com

Lumina Decision Systems 26010 Highland Way Los Gatos, CA 95033 650-212-1212 sales@lumina.com www.lumina.com

MathWorks 3 Apple Hill Drive Natick, MA 01760 508-647-7000 support@mathworks.com www.mathworks.com/products/ optimization

Maximal Software, Inc. 2111 Wilson Boulevard, Suite 700 Arlington, VA 22201 703-522-7900 703-522-7902 info@maximalsoftware.com www.maximalsoftware.com

MOSEK Fruebjergvej 3 Copenhagen 2100 Denmark +4571749373 sales@mosek.com https://mosek.com

Office of Technology Licensing, Princeton University Princeton University Princeton, NJ 08544 609-258-5308 tjvoights@princeton.edu http://www.princeton.edu/~rvdb/loqo/ index.html

OM Partners Koralenhoeve 23 2160 Wommelgem (Antwerp) Belgium +32-3-650-22-11 +32-3-650-22-90 sales@ompartners.com www.ompartners.com

OpenSolver Community help@opensolver.org http://opensolver.org

Optimalon Software Ltd.

performance, more general models, and extended interfaces.

Trends for the next two years seem likely to be a continuation of those seen previously: • Mobile computing. Look for versions that run on ARM processors, support REST services and help you build LPs into specialized apps for widespread deployment. Largescale modeling and solving might yet seem beyond the ability of phones and tablets – but the same was said about PCs at one time.

• Cloud computing. Look for services that support NEOSstyle optimization on demand, and more generally for platforms that support with equal convenience all phases of the optimization modeling lifecycle. Also expect to see cloud services become the “back ends” for those mobile apps that require extra computing power.

• Optimization. Look for software packages to further emphasize general problem-solving ability over specific algorithmic features. Expect “optimization” or “prescriptive analytics” to supplant older terms such as linear and mixed-integer programming in characterizing what these packages do. And expect software to do more of the work in reformulating problems and choosing algorithms to get the results that you’re looking for. ORMS Robert Fourer (4er@ampl.com) is president of AMPL Optimization Inc. and professor emeritus of Industrial Engineering and Management Sciences at Northwestern University.

OptiRisk Systems 1, Oxford Road Uxbridge Middlesex UB94DA UK +441895256484 info@optirisk-systems.com http://www.optirisk-systems.com/ solver_systems.asp

PuLP 2-45b Pleasant Street Onehunga Auckland 1061 New Zealand +6421441331 pulp@stuartmitchell.com https://pythonhosted.org/PuLP/

SAS SAS Campus Drive Cary, NC 27513 800-727-0025 919-677-4444 www.sas.com

Sunset Software Technology 1613 Chelsea Road Suite 153 San Marino, CA 91108 626-441-1565 jim@sunsetsoft.com

Technical University of Applied Sciences Wildau, COIN-OR c/o Prof. Mike Steglich Technical University of Applied Sciences Wildau, Hochschulring 1 Wildau D-15745 Germany mike.steglich@th-wildau.de coliop.org, projects.coin-or.org/Cmpl

Vanguard Software 1255 Crescent Green Cary, NC 27518 919-859-4101 919-851-9457 sales@vanguardsw.com www.vanguardsw.com

Virtual-Optima Perolles 90 Fribourg 1700 Switzerland tony.huerlimann@unifr.ch www.virtual-optima.com

Zuse Institute Berlin Takustr. 7 Berlin 14195 Germany scip@zib.de http://scip.zib.de

500 Hidden Creek Drive Kitchener, ON N2N3M1 Canada info@optimalon.com http://www.optimalon.com

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Software Description

Pricing Information

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Shared Memory

–

Other (s pecify)

y y – y y y y – – y

Add-in To:

Source Code

AIMMS

PC/Win dows PC/LINU X macOS

Parallel Solver Support

Other

Solver Modelin g Enviro nment Integra ted Solv er & Mo Indepen deling E dent Ap nviron. plicatio C/C++ n C#/.NET Java Python MATLAB R

Software Product Listing

Platforms Supported

Form Procedure/Class Library for:

Langua ge?

Type

–

y y y

Microsoft y – – Excel (desktop)

Free Trial

COIN-OR Foundation

52 | ORMS Today

|

June 2017

ormstoday.informs.org

–

Formulations Supported

Algorithms/Methods

SOS1, y y y y y CPLEX, Gurobi, y y y y y y y y y Lazy, CPO, XA, CBC, SOS2, Indicator, CONOPT, Knitro, SemiCompleSNOPT, MINOS, continmentarity, IPOPT, BARON, uous, Resource, PATH etc. etc.

Cloud/Software Srvc. Availability

New Features (since 2015)

Comments/description (since 2015)

S

NEOS S erver Service Provide d by Ve ndor Service Installe d by Cu stomer

Global

Local

Other A lgorithm s/Metho ds

Optimality of solutions

Simplex Interiorpoint Branch -and-cu t Local s earch

Other C onstrain t & Obje ctive Ty pes

Contraint and Objective Types

Piecew ise-line ar Quadra tic Posit ive-sem Quadra idefinite tic Conic Quadra tic Non convex Genera l Conve x Genera l Nonlin ear

Variable Types

Other va riable ty pes

Bundled as a Sin gle Pac Availab kage le Sepa rately to Continu Custom ous ers Integer, Binary

Solver or Modeling Environments Solvers appropri or modeling en v ate) tha t link to ironments (as this pro duct:

Reads S preadsh eet File Writes S s preadsh eet File Reads D s atabase Files Writes D atabase Files Reads a nd Write s Text F iles

Data Compatibility

Constraint Prog., Robust Counterpart, Stochastic Prog., etc.

y y – y y Forecasting library, R integration, collaborative data management, improved outer approximation and multistart, and more

AIMMS is used by AirLiquide, GE, Heineken etc. to deploy optimization apps across their organizations for better decision-making by end users

y y y y y y Comple- y y y y Constraint mentarity programming, constraints, global etc. optimization

y y y – – New QuanDec interface builder creates a webbased, multi-user app for sharing, analyzing, and deploying your AMPL models.

AMPL is designed for quick development & reliable deployment. It combines a powerful modeling language with access to the most advanced solvers.

y y y y y AnalyticSolver. y y y y Recourse y y y y y y AllDifferent, y y y y 12 Options: y y – – – Five major releases: com, RASON, decisions VaR, GRG, SQP, Apache Spark, Power BI, Solver SDK Expected interval, genetic Tableau, RASON support; Value algorithms, tabu/ simulation, data mining scatter search, enhancements; cloud other integration.

Best-selling Excel Solver upgrade now offers comprehensive analytics, integrates with Big Data, cloud versions, SDK, RASON modeling and REST API.

y y y y y CPLEX, Gurobi, y y y y Xpress, CONOPT, Knitro, others listed at ampl. com/products/ solvers/

y y y y y

–

– – – – – AMPL, GAMS, AIMMS, MPL, Microsoft Excel

–

– – y y Grouped y y y y y y Statistical y – y y Evolutionary y – – y y – integer constraints (genetic), and Monte Carlo objective. uncertainty analysis, intelligent arrays. y y y y

–

– – – – – AMPL, GAMS, y y y y SOS JuMP, MADOPT, OPTI Toolbox, OS

y y y y y y MPEC, MCP

y y y y Nonlinear prog. algorithms, Active Set, Sequential Quadratic Prog., etc.

Add-on solver engines also available: Frontline engines (LSLP, LSGRG, LSSQP) Gurobi, Knitro, XPress, Mosek, OptQuest.

Professional support y – y – y MISQP algorithm, R interface, Specialized provided by Artelys experts Least Square API, Hessian derivative-checker

– y – y y y

–

– – y –

Outer approximation

y – y – – –

–

–

– – y y

–

– – – – – –

–

– – y –

–

– y y – – –

– – – – y AMPL, GAMS, – y y – MPL, AIMMS

–

– – – – – –

–

y y – –

–

– y y – – –

– – – – y CBC and GLPK y y y y bundled / SCIP, Gurobi and CPLEX separately

–

Solver y – – – – – Products of y y y – variables depending with at least one integer factor

– – – – y

AMPL, GAMS, MPL, AIMMS

– y y y

–

– – – – – y

–

– – y –

–

– y – – – –

–

– – – – y

–

– – y y

–

– – – – – –

–

– – y –

–

– y – – –

–

–

– – – – y

AMPLs, GAMS, MPL, AIMSS

y y y y

– y – y y

–

Plug-in for SolverStudio, CMPL is bundled with the SolverStudio package, see: http://solverstudio. org/languages/cmpl-2/

The package contains also CMPLServer, which is an XML-RPC-based web service for distributed and grid optimization.

June 2017

|

ORMS Today

| 53

Software Description

–

MS y y y Solaris, Excel AIX, (via HPUX Frontline Solvers)

– Contact

–

Other A cademic License Availab le Free Lim ited-siz e Versio ns Avail able Free Fu ll-featu red Vers ions Ava ilable Free /O pen-sou rce for All Users

License Other C ommerc ial Lice nse Ava ilable Academ ic Single License

y

Comme rcial Sin gle

Other (s pecify)

PC/Win dows PC/LINU X macOS

Add-in To:

–

Langua ge?

–

Distribu ted Mem ory

y y y y y y y y y –

Fair Isaac Corporation

Pricing Information

Parallel Solver Support

Shared Memory

FICO® Xpress Optimization Suite

Source Code

Solver Modelin g Enviro nment Integra ted Solv er & Mo Indepen deling E dent Ap nviron. plicatio C/C++ n C#/.NET Java Python MATLAB R

Software Product Listing

Platforms Supported

Form Procedure/Class Library for:

Other

Type

Free Stud. Yes aca- ver. demic (size pro- restricgram ted)

No

–

No

–

(full ver.)

FortSP

y – – y y – – – – –

–

–

–

–

y y y

–

–

– Contact Contact Contact Contact Contact

GAMS

– y y y – – – – – –

–

–

–

–

y y y

AIX, Solaris (Intel, Sparc)

y

– $3,200 www. $640 www. gams. gams. com com

Yes

GENO 2.0

y – – y – – – – – – GAUSS

– GAUSS

GAUSS

y y y

–

–

– Contact Yes Contact Yes info@ info@ aptech aptech .com .com

No

No

–

GIPALS32

y – – – y y – – – – Delphi

– Delphi

–

y – –

–

–

– $179 $1,997 for unltd. number of users

GLPK (GNU Linear Programming Kit)

y y y y y – – – – –

–

y ANSI/ISO C 89

–

y y y Any 32- or 64-platform supporting ANSI/ISO C 89

–

–

–

hsol

y – – – – – – – – –

–

y C++

–

y y y

y

–

–

y

y From Yes, Free Free Com- Yes $10K Contact for re- for re- munity for 1 search search Edition identand and ified teach- teachuser ing ing

OptiRisk Systems

GAMS Development Corp.

Aptech Systems Inc.

Optimalon Software Ltd.

Free Software Foundation, Inc.

Julian Hall

–

Time- – limited evaluation

–

–

Free trial for 30 days

–

–

–

–

–

–

–

y

–

–

–

–

–

y

IBM ILOG CPLEX Optimization Studio

y – y y y y y y y –

–

–

Ipopt

y – – y y y y y y y

–

y C++

–

– y y

–

–

–

–

–

–

–

–

–

y

JuMP

– y – – – – – – – –

Julia

y Julia

–

y y y

–

–

–

–

–

–

–

–

–

y

LINGO

– – y y y y y y y y VB.NET, VBA

Excel

y y y

–

y

– Varies Contact Free Contact Yes with capacity/ from $495

IBM

COIN-OR

JuliaOpt

LINDO Systems, Inc.

54 | ORMS Today

|

June 2017

–

–

–

GAMS, y y y AIX, z/OS, AMPL, zLinux, AIMMS, pLinux MATLAB

–

For – evaluation purposes

ormstoday.informs.org

Formulations Supported

Algorithms/Methods

y y y y y FICO® Xpress y y y y UncerMosel, AMPL, tain Frontline Systems, GAMS, Matlab

y y y – y y Black-box

– – – – – AMPLDev

–

y y y – Constraint prog., robust optimization, sensitivity analysis, heuristics

New Features (since 2015)

Comments/description (since 2015)

S

NEOS S erver Service Provide d by Ve ndor Service Installe d by Cu stomer

Global

Local

Cloud/Software Srvc. Availability

y – y y y Parallel innovations: task-based MIP search, parallel crossover, parallel black-box and derivative evaluations.

Xpress is a comprehensive set of fast solvers with modeling and optimization solution building, deployment and management - on cloud and on prem.

– – – – – Branch and cut addition to SIP processing capability.

The enhanced solver has been tested on SSD long/ short portfolio models.

Uses L-shaped method to process single stage and two-stage stochastic programming models. The embedded solvers are: CPLEX, Gurobi, FortMP.

y – y – y https://www.gams. com/latest/docs/ releasenotes/24.8.html

–

y y – – y Now solves systems of linear/nonlinear equations; it also accommodates real discrete variables and specific search points.

GENO solves uni-/multiagent, static/dynamic optimization problems, with or without equation constraints, for continuous or discrete solutions.

–

– – – – – –

–

LP/MIP preprocessing, MIP heuristics, transforming MIP to CNF-SAT

– y – – – –

–

– y – – – New product

Terms of open-source availability yet to be decided. Source is available on application

y y y y y Model assistance, variability tester, automated benders decomposition, cloud solve service, objectoriented Python API

CPLEX Optimization Studio features a Development Env. for OPL and 2 engines, CPLEX (math progr.), CPOptimizer (constraint progr., scheduling)

y y y y

–

– – – – – –

y y y y y All major y y y y solvers: https:// www.gams. com/fileadmin/ commercialp. pdf

–

y y y y y y Mixedy y y – integer-nonlinear

– y – –

– – y y y

GAUSS

– – – – y

–

– – y –

–

– – – – – –

–

– y – –

y y y y y

–

– – y y

–

– – – – – –

–

y y y –

– – – – y

SCIP

– – y –

–

– – – – – –

–

y – – –

y y y y y

Other A lgorithm s/Metho ds

Optimality of solutions

Simplex Interiorpoint Branch -and-cu t Local s earch

Other C onstrain t & Obje ctive Ty pes

Contraint and Objective Types

Piecew ise-line ar Quadra tic Posit ive-sem Quadra idefinite tic Conic Quadra tic Non convex Genera l Conve x Genera l Nonlin ear

Variable Types

Other va riable ty pes

Bundled as a Sin gle Pac Availab kage le Sepa rately to Continu Custom ous ers Integer, Binary

Solver or Modeling Environments Solvers appropri or modeling en v ate) tha t link to ironments (as this pro duct:

Reads S preadsh eet File Writes S s preadsh eet File Reads D s atabase Files Writes D atabase Files Reads a nd Write s Text F iles

Data Compatibility

Level decomposition

–

y y y y Real y y y y – y Multiple – – – – Evolutionary discrete Objectives; Algorithm variables Procedural Objectives

–

GAMS, y y y y Semi- y y y y y y Logical y y y y Edge-finder, all AMPL, AIMMS, continconstraints, different, other MATLAB uous, scheduling propagation etc. constraints algorithms

– – – – – AIMMS, y y y – AMPL, CasADi, GAMS, JuMP, MADOPT, OPTI Toolbox, OS, Scilab

–

– y – y y y

–

– y – –

–

y – y – – –

–

– – – – –

See http://www. juliaopt.org/

–

– y y y y y

SDP

– – – –

–

– – – – – Syntax improvements, user-defined nonlinear functions, semidefinite programming.

Fast and extensible opensource algebraic modeling language.

y y y y y

MATLAB, LINDO API

y y y – y AllDifferent constraint support. Improved performance on fixed charge/min batch size/ cardinality constraints.

Fast linear, integer, nonlinear, quadratic, stochastic and global solvers and a comprehensive modeling language with convenient data options.

– y y y

y y y y Semi- y y y y y y AllDifferent y y y y SOC, SDP, GRG, continconsraints, Global, Benders. uous, Chance Extensive Stochconstraints, heuristics to astic POSD, SOS2, give good initial Logical, etc. solutions fast.

June 2017

|

ORMS Today

| 55

Software Description

y – – y y – – – y –

–

–

–

AMPL

y y y

LPL Modeling System

– y y y y y y – – –

–

–

–

–

MATLAB and Optimization Toolbox

y y y y – – – – y – Integration – with Java, .NET, C/ C++, Fortran and Python

–

MibS (Mixed Integer Bilevel Solver)

y – – y y – – – – –

–

MOSEK Optimization Suite

y – – y y y y y y y

Julia

–

–

MPL Modeling System

– y y y y y y y y –

–

–

–

OMP Plus

y y y y – – – – – –

–

–

–

OpenSolver

– – y – – – – – – –

–

PuLP

– y – – – – – y – –

Pyomo

y y y – – – – y – –

Office of Technology Licensing, Princeton University

Virtual-Optima

MathWorks

Lehigh University

MOSEK–

Maximal Software, Inc.

OM Partners

OpenSolver Community

Free open source

Open Source

56 | ORMS Today

|

June 2017

y C++

Other A cademic License Availab le Free Lim ited-siz e Versio ns Avail able Free Fu ll-featu red Vers ions Ava ilable Free /O pen-sou rce for All Users

LOQO

y y y Oracle Solaris 11 (x64)

License Other C ommerc ial Lice nse Ava ilable Academ ic Single License

–

Comme rcial Sin gle

–

Distribu ted Mem ory

–

Shared Memory

–

Other (s pecify)

PC/Win dows PC/LINU X macOS

y – y y y y y y – –

Add-in To:

Source Code

LocalSolver LocalSolver

Pricing Information

Parallel Solver Support

Other

Solver Modelin g Enviro nment Integra ted Solv er & Mo Indepen deling E dent Ap nviron. plicatio C/C++ n C#/.NET Java Python MATLAB R

Software Product Listing

Platforms Supported

Form Procedure/Class Library for:

Langua ge?

Type

y

– 9,900 contact Free Contact 1-mnth 1-mnth – Euro @local @local trial trial solver. solver version com .com

–

–

– $2,000

–

$300

–

–

–

–

y – –

–

–

– 4,000 Euro

Call

100 Euro

Call

Yes

–

–

Excel

y y y

–

y

y Contact Contact Contact Contact Concurrent, classroom, campus

–

y y y

–

–

–

–

y y y

–

y

Cplex, y y y Gurobi, Xpress, Lindo, Mosek, etc.

–

–

–

–

Trial – version

–

–

–

–

y

– Start- Yes ing at $1,950

Free

Free

–

No

–

y

– Start- Contact ing at $3,900 or sub. $780/yr

MPL Per- Student MPL – Free petual ver.: Free Acad. Acad., 300 DevelProg. Dept. x 300 opment SiteProLicense gram

–

y – –

–

y

– Contact Contact Contact Contact Contact Contact –

y Visual Basic

Excel

y – y

–

–

–

–

–

–

–

–

–

y

–

y Python

–

y y y

–

–

–

–

–

–

–

–

–

y

–

y Python

–

y y y

–

–

–

–

–

–

–

–

–

y

ormstoday.informs.org

Formulations Supported

Algorithms/Methods

y y – – y

AMPL, GAMS

y y y y List

– – – – y

AMPL

y y y –

–

– – – – y y

y y y y y

–

– – y y

–

y y y y y Gurobi, – y y y CPLEX, Xpress, Mosek, Knitro, AMPL, CVX, Yalmip, and others

–

– – – – y

–

– – y y

–

– – – – – – Optimality – – y – constraints for bilevel programming

– – – – y

AMPL, GAMS

– y y y

–

– y y – y – Semidefinite problems

y y y y y y Set-related y – y y Constraint constraints propagation & inference techniques, nonlinear prog. techniques.

–

–

New Features (since 2015)

Comments/description (since 2015)

S

NEOS S erver Service Provide d by Ve ndor Service Installe d by Cu stomer

Global

Local

Cloud/Software Srvc. Availability

y y – – y Dynamic roadmap to deliver new features and performance improvements: two versions per year released since 2012.

LocalSolver is an all-terrain, all-in-one mathematical solver, for large-scale, real-life combinatorial and numerical optimization.

– y – –

–

– – y – – –

–

y y y y y y Logical

– – – –

–

– – – y – –

–

– y y y y y Multiobjective

y y y

y – – y y Improved speed and robustness for mixedinteger, linear, quadratic and nonlinear solvers.

Combine Optimization Toolbox with MATLAB data preprocessing, predictive modeling, and graphics to build and deploy optimization applications.

–

– y – – – –

–

y y y –

–

– y – – – Version 8 was released in 2016.

–

y y y y

Heuristics Search, Infeasibility Diagnosis, Stochastic Programming

y y y y y New MPL release 6.0, offers a large MPL C-API Callable Library with over 500 functions and full support for Multithreading

Maximal offers full-size development copies of MPL for FREE, through our MPL Free Development and MPL Academic Programs.

–

y y y y

–

– y – – – –

–

y y y y y Cplex, Gurobi, y y y y Semi- y – – y y y Global Xpress, Lindo, ContinMosek, Sulum, uous, XA, CoinMP, SOS, Ipopt, Glpk, StochaLPSolve, etc. stic y y y y y

Other A lgorithm s/Metho ds

Optimality of solutions

Simplex Interiorpoint Branch -and-cu t Local s earch

Other C onstrain t & Obje ctive Ty pes

Contraint and Objective Types

Piecew ise-line ar Quadra tic Posit ive-sem Quadra idefinite tic Conic Quadra tic Non convex Genera l Conve x Genera l Nonlin ear

Variable Types

Other va riable ty pes

Bundled as a Sin gle Pac Availab kage le Sepa rately to Continu Custom ous ers Integer, Binary

Solver or Modeling Environments Solvers appropri or modeling en v ate) tha t link to ironments (as this pro duct:

Reads S preadsh eet File Writes S s preadsh eet File Reads D s atabase Files Writes D atabase Files Reads a nd Write s Text F iles

Data Compatibility

– – y y Semi- – – – – – – Continuous, PartialInteger

Sequential quadratic prog., trust region, LevenbergMarquardt, Nelder-Mead

y y – – – CBC, NEOS, BonMin, Couenne, Gurobi

y – y y

–

– – – – – –

–

y y y –

–

– y – – – Improved non-linear support. Available for Macintosh as well as Windows. Better solver integration. Usability enhancements.

Open source Excel plug-in for building & solving optimization models in spreadsheets. Comes with open source solvers.

Supports Gurobi & NEOS.

y y y y y CBC, Gurobi, CPLEX

– y y y

–

– – – – – –

–

– – – –

–

– – – – – –

Supported by and part of https://www.coin-or.org/

– – y –

–

y y y y y y Comple- – – – – mentarity conditions, generalized disjunctions

–

y y – – – Releases 4.1, 4.2 , 4.3, 4.4, 5.0 and 5.1. Added support for Python 3.6, support for new solvers and conda installation.

Pyomo is an open-source software package that supports a diverse set of capabilities for formulating and analyzing optimization problems.

y – y – y

–

June 2017

|

ORMS Today

| 57

Software Description

RASON: Restful Analytic Solver Object Notation

–

Frontline Systems Inc.

y y y – – – – – – – REST API – - Optimization as a Cloud Service

SAS Optimization 8.1

y y y y – – y y – y

SAS – programming language; Lua

–

SCIP

y – – y y – y y y – Julia

SolverStudio

– – y – – – – – – –

–

–

SoPlex

y – – y y – – – – –

–

SYMPHONY

y – – y y – – y – y

–

The Gurobi Optimizer Gurobi Optimization, Inc.

y y y y y y y y y y Visual – Basic and Julia

Vanguard System

y y y y – – – – – y

What’sBest!

– – y y – – – – – –

XA Professional Linear Programming System

y – – – y y y y y y Fortran

ZIMPL

– y – y y – – – – –

SAS

Zuse Institute Berlin

SolverStudio

Zuse Institute Berlin

COIN-OR Foundation

y C, C++

LINDO Systems, Inc.

VBA

58 | ORMS Today

|

June 2017

–

–

Other A cademic License Availab le Free Lim ited-siz e Versio ns Avail able Free Fu ll-featu red Vers ions Ava ilable Free /O pen-sou rce for All Users

License Other C ommerc ial Lice nse Ava ilable Academ ic Single License

Comme rcial Sin gle

Distribu ted Mem ory

Shared Memory

Other (s pecify)

y y y Browsers, web servers, mobile apps

SAS – y – Visual Analytics

y

– $97 to Contact $297 vendor per month

–

Yes

–

y

y Contact Yes Contact Yes Contact Contact

No

Yes

–

Free – trial at www. sas. com

y y y

–

y

– Contact

Excel

– – –

–

–

–

y C++

SCIP

y y y

–

–

– Contact Yes

y C++

–

y y y

–

y

y

AIX

y

y See Floating, Free Float- Yes web- Coming & site pute site Server, licenses etc.

y

y Call for pricing

y

– Varies Contact Free Contact Yes with capacity/ from $495

y

– Contact Contact Contact Contact Contact Contact –

–

– Free

–

–

–

–

– C/C++

MS Excel y y y (via Frontline Solvers) etc.

–

y

C

y – – Web-based UI

Excel

y – –

Excel

y y y Raspberry Pi

Sunset Software Technology

Zuse Institute Berlin

PC/Win dows PC/LINU X macOS

Add-in To:

–

–

Web y DScript Services API (SOAP/ REST)

Vanguard Software

Pricing Information

Parallel Solver Support

Langua ge?

Other

Solver Modelin g Enviro nment Integra ted Solv er & Mo Indepen deling E dent Ap nviron. plicatio C/C++ n C#/.NET Java Python MATLAB R

Software Product Listing

Platforms Supported

Form Procedure/Class Library for:

Source Code

Type

–

y y y

–

–

–

–

No

$0

No

No

Yes

–

–

–

–

–

–

y

$0

Yes

No

Yes

–

–

–

–

–

y

Yes

–

–

–

–

Call for pricing

Free

–

–

Free Free – Trial/ Trial/ Demo Demo

–

For – evaluation purposes

–

ormstoday.informs.org

y

Formulations Supported

Algorithms/Methods

Cloud/Software Srvc. Availability

y y y y y Analytic Solver, y y y y Recourse y y y y y y AllDifferent, y y y y 12 Options: y y – y – Solver SDK decisions VaR, GRG, SQP, Expected interval, genetic Value algorithms, tabu/ scatter search, other y y y y – OPTMODEL, y y y y OPTLP, OPTQP, OPTMILP, Contact SAS directly.

–

– y – y y y

–

y y y y Automated Dantzig-Wolfe decomposition; network optimization algorithms.

– – – – y GAMS, AMPL, ZIMPL, GCG, UG, PolySCIP, SCIP-SDP, Comet, G12, or-tools

y y y y

–

y y y y y y Indicator, y – y – Column logic, generation, cumulative, branch-andand price, solution cardinality counting constraints

New Features (since 2015)

Comments/description (since 2015)

Major releases in March 2015, mid-2016, early 2017. Modeling language enhanced, higher performance in every Solver Engine.

RASON models, embedded in JSON and solved in the cloud via a REST API, radically simplify the creation of optimization-based web and mobile apps.

S

NEOS S erver Service Provide d by Ve ndor Service Installe d by Cu stomer

Global

Local

Other A lgorithm s/Metho ds

Optimality of solutions

Simplex Interiorpoint Branch -and-cu t Local s earch

Other C onstrain t & Obje ctive Ty pes

Contraint and Objective Types

Piecew ise-line ar Quadra tic Posit ive-sem Quadra idefinite tic Conic Quadra tic Non convex Genera l Conve x Genera l Nonlin ear

Variable Types

Other va riable ty pes

Bundled as a Sin gle Pac Availab kage le Sepa rately to Continu Custom ous ers Integer, Binary

Solver or Modeling Environments Solvers appropri or modeling en v ate) tha t link to ironments (as this pro duct:

Reads S preadsh eet File Writes S s preadsh eet File Reads D s atabase Files Writes D atabase Files Reads a nd Write s Text F iles

Data Compatibility

y y – y y New offering. MILP: distributed concurrent mode. Network optimization: 2 distrib. algorithms, distrib. BYgroup processing.

Part of SAS Viya platform.

Integrated with broad suite of products for descriptive and predictive analytics and data exploration/ visualization.

– y y – – https://opus4.kobv.de/ opus4-zib/frontdoor/ index/index/docId/6217

Available as package together with LP solver SoPlex, modeling language ZIMPL, generic branch-andprice solver GCG, massive parallel framework UG

– y – – – Now also supports Julia/ JuMP

Use modelling languages such as AMPL, Julia/JuMP, PuLP, Pyomo & GAMS to build & solve optimization models within Excel.

– y y – – LP solution polishing, decomposition-based dual simplex, persistent scaling

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– y y – – –

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y y y y y Support for multiple objectives, MIP solution pools and new general constraints. Significant python modeling enhancements.

Superior optimization algorithms, flexible interfaces, technical support from optimization experts, transparent pricing and flexible licensing.

y y y y y Standard and – – y y Stocha- y y y y y y Stochastic y – – y Proprietary proprietary stic algorithms/ solvers and methods modeling environment

y y – y – Vanguard’s optimzation capability is integrated in our flagship planning and forecasting application, Vanguard IBP.

Vanguard is used by over 3,400 customers in 68 countries and for supply chain, finance, sales, human capital, IT, and advanced analytics.

y y – – – LINDO API

y – y y Semi- y y y y y y AllDifferent y y y y SOC, SDP, GRG, continconsraints, Global, Benders. uous, Chance Extensive stochaconstraints, heuristics to stic POSD, give good initial SOS2, etc. solutions fast.

y y y – y AllDifferent constraint support. Improved performance on fixed charge/min batch size/ cardinality constraints.

What’sBest! is a large scale optimization add-in for Excel; powerful enough for real-world models and ideal for building models for clients.

– – y y Semi- – y – – – – continuous

y y – – –

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– – y y

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y y y y y y

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y y y –

– – – – y

SCIP

y y y –

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y – – – Scaling, row basis, iterative refinement, LP solution polishing, exact solving

– – – – y

AMPL, GAMS

– y y y

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– – – – – –

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– – y –

y y y y y

AIMMS, AMPL, GAMS, MATLAB, MPL, CVX and Frontline Solvers

y – y – y

AIMMS, GAMS, AMPL, MPL

– – – – y

SCIP, lp_solve

–

–

y y y y Semi- y y y – – – SOS y y y y Presolve, sifting, continconstraints, feasRelax, uous, lazy sensitivity semiconstraints analysis, integer infeasibility analysis

y y y y

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– – – y y y

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y y y –

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y y – – –

Raspberry Pi Edition in support of Internet Of Things (IoT)

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June 2017

Supports 32/64bit IoT micro-controllers

GNU LGPL license

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Industry News

AIMMS, UniSoma, CAT Squared form global partnership AIMMS, a vendor of prescriptive analytics software, and UniSoma, a provider of advanced planning solutions, announced a global partnership with CAT Squared, a company that specializes in innovative software solutions designed specifically for the food industry.

The partnership will enable AIMMS, UniSoma and CAT Squared to provide prescriptive analytics applications for food processing and production companies.

CAT Squared customers include leading enterprises in beef, pork, chicken, turkey, seafood and produce processing and handling.These companies are already collecting real-time data from the plant floor and are equipped with real-time reporting for production and inventory and farm-to-fork traceability.

UniSoma’s expert consultants are experienced at working with global companies in the food industry as well.

UniSoma has been a longtime AIMMS partner. Through their partnership, the companies have enabled food industry giants like Marfrig and JBS to develop planning that generate significant business value.

The initial solution developed through this new partnership will be a tactical planning application for customers that use CAT Squared solutions to monitor and manage data.The AIMMS PRO platform and CAT Squared’s software suite will be tightly integrated to empower customers with a better planning tool. Supported by UniSoma’s knowledge in optimization models and in leveraging existing data, these companies will be better equipped to overcome barriers in traditional MRP systems by truly representing the dissembling process characteristics of the business and ensuring that planning decisions have a substantial positive effect on their margin.

What’sBest! new release offers many enhancements Release 14 of What’sBest! includes a wide range of performance enhancements and new features, including: • Faster solutions on linear models with improved simplex solver • Improved integer solver with new features 60 | ORMS Today

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June 2017

• Enhanced stochastic solver • Improved global solver • New scenario viewer The new release includes additional enhancements, including improved model validity checking and more comprehensive error messages, new features to summarize location of the adjustable and constraint cells in the workbook to ease the understanding of the model, and added support for the standard deviation function STDEV. Woolpert, FICO partner to help agencies meet cybersecurity order Woolpert, a U.S. architecture, engineering and geospatial firm, has joined the FICO Enterprise Security Score partner program and will incorporate the score into its EC:Secure portfolio of products and services. This will allow Woolpert’s governmental and national security clients to accurately and effectively assess their cybersecurity risk.

“Under the recent Presidential Executive Order (E.O. 13800) on Strengthening the Cybersecurity of Federal Networks and Critical Infrastructure, all U.S. federal agencies need to take further steps to improve protection,” said Kim Hansen, Woolpert’s national security marketing manager.“We’re taking FICO’s advanced analytics to the federal government and enabling agencies to benchmark their performance, as well as that of their partners and vendors. It’s all part of keeping America safe.”

The FICO Enterprise Security Score provides an easy-to-understand metric that facilitates board-level risk assessment, thirdparty vendor management, and cyber breach insurance underwriting.Along with a score, the product provides current threat profile characteristics and granular insights into potential security issues to facilitate security posture remediation and continuous improvement processes. The score also helps organizations manage cyber-risks from vendors, business partners and other third parties.

In generating the Enterprise Security Score, FICO uses supervised machine learning algorithms to analyze thousands of components of an organization’s cybersecurity posture and behavior over time, and correlate these with observed data breach patterns.

The result is an empirically derived view

into cyber risk based on real mathematical equations, rather than arbitrary judgments or categorical assignments of points or grades.

The score is based on data that is continuously collected at internet scale, allowing users to leverage the score and the underlying data infrastructure for continuous monitoring of risk – and ongoing remediation of issues – as threats, conditions and organizational behaviors change over time.

“The guidelines in the president’s executive order on cybersecurity line up perfectly with the FICO Enterprise Security Score,” said Doug Clare, vice president of cybersecurity solutions at FICO.“Woolpert is taking a leadership role in bringing these capabilities to government agencies.”

Optimization Direct creates new algorithm for massive MIP models With bigger and more global data sets, customers are presenting increasingly large and complex models to optimize. With these massive models, established optimization technology generally fails in that it can either find no solution at all or solutions that take too long to find or are too poor to have any value. ODHeuristics, a new algorithm created by Optimization Direct, is designed to run on modern multiprocessor machines.

Many cores (24+ ideal) are exploited by the ODHeuristics engine by breaking complex models and difficult MIPs into sub-models and solving them in parallel threads.

Optimization Direct has combined the new algorithm with CPLEX in the ODH-CPLEX Optimizer specifically to find solutions to massive MIP models of the big data era.The ODHeuristics engine is run under CPLEX in both deterministic or opportunistic modes; the combination of the two requires more memory and processor resources, but ODH accelerates CPLEX and helps CPLEX heuristics and finds good solutions to these massive data sets.

ODHeur istics is designed for scheduling problems but works for any MIP that has a reasonable number of integer feasible solutions. It has been deployed effectively on packing problems, supply chain and telecoms as well as scheduling applications. On large-scale MIPs it provides good solutions and optimality measures that are often beyond the reach of traditional optimization methods. ORMS ormstoday.informs.org

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FACULTY RECRUITMENT ADVERTISEMENT Applications are invited at Amrut Mody School of Management, Ahmedabad University for candidates in fields of Business Analytics, Big Data Analytics, Information Systems, Operations Management, Operations Research, Statistics, Supply Chain Management and Technology Management.

Amrut Mody School of Management (AMSOM) has over 2500 students across various programmes under the umbrella of Management, covering the entire range from undergraduate to Doctoral degrees and certificate programmes for practitioners. We invite applications for faculty positions at all levels.

Candidates at the Assistant Professor level must demonstrate capability for carrying high quality research, and should have completed Ph.D. However, those who are in the final stage of their PhD can also apply. Associate Professors should have a track record of research and teaching. Professors are additionally expected to provide academic leadership at the School.

ABOUT AHMEDABAD UNIVERSITY Ahmedabad University (AU) is a private, non-profit, liberal education driven research university rapidly developing into a serious center for scholarship. Since its inception in 2009, the University has made strides through global collaborative research, broad based contextual and flexible curriculum, project based learning, and industry linkages; thus creating a unique learning opportunity.

Interested candidates may send following details to deanamsom@ahduni.edu.in.

1. A curriculum vitae( CV) 2. List of references 3. Samples of recent research output including a job market paper Information about Ahmedabad University and AMSOM is available at www.ahduni.edu.in.

THE HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY

Faculty Positions Department of Industrial Engineering and Logistics Management The Department of Industrial Engineering and Logistics Management invites applications for substantiation-track faculty positions in the area of (i) Predictive and Prescriptive Analytics, (ii) Healthcare and Sports Analytics, (iii) Financial Engineering and Fintech, and (iv) Demand and Supply Analytics.

Applicants must have a PhD degree in Industrial Engineering, Operations Research, or a closely related area. The appointee is expected to demonstrate strong potential for effective teaching and promising research in the respective fields.

Appointments at all ranks (Assistant Professor/ Associate Professor / Professor) will be considered. Salary is highly competitive and will be commensurate with qualifications and experience. Fringe benefits include annual leave, medical and dental benefits. Housing benefits will be provided where applicable. Appointment at Professor rank will be on substantive basis. Initial appointment for Assistant Professor/Associate Professor will normally be made on a 3-year contract. A gratuity will be payable upon successful completion of contract. Strong candidates applying for Associate Professor position may also be considered for appointment on substantive terms.

Applications with a full C.V.; statement of research and teaching; transcript of graduate work; copies of 2 research publications; names, emails and addresses of at least three referees, should be directed to the Search and Appointment Committee, Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong [email : ielm@ust.hk]. Review of applications will start immediately and continue until the positions are filled.

More information about the Department can be found at http://www.ielm.ust.hk.

The Thomas J. Watson School of Engineering and Applied Science at Binghamton University is seeking nominations and applications for the George J. Klir Endowed Professor in Systems Science. This is a newly-created position made possible by a gift to honor the memory and work of the late George J. Klir, a Distinguished Professor Emeritus of Systems Science at Binghamton University.

The candidate should demonstrate leading academic fortitude in the fields inspired by Dr. Klir's work including, but not limited to: complex systems; cybernetics; fuzzy set theory, fuzzy logic and fuzzy systems; general systems concepts and theory; generalized information theory; probabilistic and possibilistic theory; soft computing; systems problem solving; uncertainty theory; and fields and disciplines that develop from this work.

The position will carry the rank of full professor in the Department of Systems Science and Industrial Engineering (SSIE). Other attributes of the desired candidate include international stature and visibility; a history of recognized teaching and scholarship; and a reputation as a respected leader and mentor for graduate students and post-doctoral researchers.

The incumbent will be expected to document his or her accomplishments in these areas on a yearly basis to the Chair of the SSIE Department as well as the Dean of the Watson School, and the cumulative contributions will be evaluated for the purposes of reappointment to the named professorship by the Provost at five year intervals.

The SSIE Department currently has 20 faculty members and offers a BS degree in Industrial and Systems Engineering, and MS and PhD degrees in both Systems Science and in Industrial and Systems Engineering. With about 235 undergraduate, 230 Masters, and 120 doctoral students, the Department is rapidly growing in numbers and in reputation. More details about the department are available at http://www.binghamton.edu/ssie/.

The Thomas J. Watson School of Engineering and Applied Science is one of the fastest growing engineering schools in the nation, with 1921 undergraduates and 1188 graduate students. The Watson School is home to nationally and internationally recognized faculty scholars and has several affiliated research centers and organizations. The Watson School is now poised to take a quantum leap to establish itself as a highly visible research-intensive school within a premier public university. The Watson School is dedicated to the goal of building a diverse and inclusive teaching, research, and working environment. Potential applicants who share this goal, especially underrepresented minorities, women and persons with disabilities, are strongly encouraged to apply.

Binghamton University is a highly ranked "Public Ivy." Binghamton University has built a reputation as a world-class institution that combines a broadly interdisciplinary, international education with one of the most vibrant research programs in the nation.

Binghamton is proud to be ranked among the elite public universities in the nation for challenging our students academically, not financially. The result is a unique, best-of-both-worlds college experience.

Applications and nominations should include full contact information, a complete CV, cover letter, research and teaching statements, and the names of three professional references. Review of applications will begin on August 1st, but the position will remain open until filled. Application materials or nominations may be sent to Dr. John S. Bay, Associate Dean for Research and Graduate Studies, bayj@binghamton.edu.

June 2017

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UNITED PARCEL SERVICE UPS is looking for Operations Research and Advanced Analytics professionals in Atlanta, GA. » Leading edge optimizations and analytics-based decision support tools » Complex models and algorithms that impact cost and efficiency for operations » Real world challenges applying advanced mathematical techniques and technology » Winning team working on top tier enterprise projects INTERESTED? Follow links for how to apply. www.jobs-ups.com/job/alpharetta/lead-or-analyst/1187/3870779 www.jobs-ups.com/job/alpharetta/advanced-analytics-manager/1187/3909098 UPS (NYSE: UPS) is a global leader in logistics, offering a broad range of solutions including the transportation of packages and freight; the facilitation of international trade, and the deployment of advanced technology to more efficiently manage the world of business.

Headquartered in Atlanta, UPS serves more than 220 countries and territories worldwide.

advertiser index

H T T P : / / W W W. A N A LY T I C S - M A G A Z I N E . O R G

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DRIVING BETTER BUSINESS DECISIONS

M AY/JUN E 2017

B2B

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C2

3

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AIMMS

1

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Frontline Systems, Inc.

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C4 GAMS Development Corp.

13

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info@optirisk-systems.com www.optirisk-systems.com

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ALSO INSIDE:

Executive Edge Heine Krog Iversen, CEO of TimeXtender, on why data professionals must move up corporate ladder

• New paradigm: Service as a software • Big data & better business decisions • How to transition from CSP to DSP • Healthcare analytics: What’s next?

• Storytelling skills: The write stuff • Corporate profile: Praxair model

713.87.9341 info@gurobi.com www.gurobi.com

7, 9, 11, INFORMS 15, 17, informs@informs.org 18, 33, meetings@informs.org 37, 38 www.informs.org

Check out the May/June 2017 Issue of Analytics Now Available at: www.analytics-magazine.org

June 2017

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ORMS Today

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ORacle

Doug Samuelson

samuelsondoug@yahoo.com

The neighborhood watch parable The community pool had reopened for the summer with the annual Memorial Day party, and the group of neighbors was catching up on all sort of topics. Although they lived close to each other, it seemed they didn’t chat much except for occasions like this one, or the rare time when some crisis called them together.

“Glad I wasn’t flying to London this week,”Tom spoke up.“Did you hear about what happened with British Airways?”

“No kidding!” Gladys chimed in.

“You hear about terrorists killing a few people here or there as if it was the biggest news story of the week, but not the hundreds of other murders. And tens of thousands of people stranded for who knows how long? Not so much. I guess the video isn’t as dramatic.”

“Or the politicians can’t make as much out of blaming it on someone,” Bob interjected slyly.

“Not that some of them haven’t been trying,” Gladys laughed. “But once the follow-up news stories indicated that this probably wasn’t a terrorist hack, I guess it wasn’t as exciting.”

“Too bad,” said Jean, who they knew was an OR/MS analyst with national security experience. “Because in terms of lessons learned about what to do differently, the airline scheduling glitch is by far the more important story.”

“How so?” several people asked quickly.

“It’s a little early to be sure,” Jean explained, “but it definitely looks as if what happened was that the airline had outsourced some key components of their IT software to an overseas company. The components met specifications, but in view of the geographical and cultural distance, they just sort of economized on testing the integrated system before they went live on a busy weekend. And they showed once again why you don’t want to approach IT upgrades, or any other big project, that way!”

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“Hmm, OK,”Tom acknowledged.“But what makes that story so important?”

“Companies and governments do this all the time,” Jean responded. “Remember how Mitt Romney’s get-out-the-vote software crashed in 2012, and it turned out they had never tested it at anywhere near the scale of operations they planned?

Or you may have heard about defense spending cutbacks.What you don’t hear is that the first items cut are usually benefits, training and travel – especially training and travel for joint exercises. The idea is, just focus on improving each unit’s capabilities and everything will get better.

Right?”

The others nodded, somewhat uncertainly.

“But we know from past military experience,” Jean went on, “that the joint exercises are the most critical! When they’re in a threatening situation they didn’t train for, commanders become much more cautious and less decisive – so, less effective – when they don’t know the commanders of the units operating near them. These joint exercises, including the little beer drinking sessions afterward that never make it into the wrap-up report, turn out to be extremely important to success! And that makes me really worried about this current doctrine of equipping units to be better and better at more and more tasks but spending much less time and resources training them to collaborate.”

Tom agreed, “We see that with emergency responders, too. The bigger the emergency, the more everyone needs to cooperate – know who’s doing what, know who has resources you need, know which other units you can rely on. And the bigger the emergency, and therefore the broader the cooperation you’ll need, the less likely it is that anyone wants to pay for the joint training exercise. Back during the 1990s, FEMA paid for a lot of joint training exercises with state and local

responders, and they clearly helped quite a bit. As one local fire chief put it one time at a conference I attended, ‘When I’m in the middle of directing the response to a big fire, that’s not the time for the local FEMA director to walk up and introduce himself – much less introduce himself and then start telling me what to do.’”

“We see this at the hospital, too,” Gladys added. “Doctors, techs and even some nurses get more and more specialized, and they’re all very good at what they do, but once there’s agreement about a diagnosis and course of treatment, it’s easy to miss when something else happens – because people focus in on what they know best.”

“I saw this on an airline a few years ago,” Tom said. “I was traveling with a serious but manageable health problem.

As I got back from a toilet trip, a flight attendant was crouching next to the passenger in the next seat, helping her deal with an asthma attack. The flight attendant told me I’d have to stand for a few minutes and then change seats. I didn’t get a chance to object. But then another flight attendant came up behind me, pushing a beverage cart, and rather sharply ‘requested’ that I get out of the way! He couldn’t see the other flight attendant and didn’t know there was a medical problem there – in short, no coordination between responders, and no idea of what to do if they had two sick passengers at once in the same row of seats! Not good!”

“So how do we improve this?” Bob inquired.

“We’re doing it, at least for crime prevention and emergency response in our neighborhood,” Jean replied, waving her hand at the gathering. “We get to know each other at casual events, so we react when we see someone unfamiliar acting in a suspicious way in the neighborhood, and when there’s a blizzard, we know who has the snow blowers and the four-wheel-drive SUVs. Community-building is underrated, but it works!” ORMS Doug Samuelson (samuelsondoug@yahoo. com) is president and chief scientist of InfoLogix, Inc., in Annandale, Va.

ormstoday.informs.org

G A M S - R E L AT E D C O U R S E S AND WORKSHOPS IN 2017 Whether you are new to GAMS or already an experienced user looking to deepen or expand your knowledge in a certain area – take a look at our diverse list of GAMS-related courses.

Learn advanced, state-of-the-art techniques in a focused and interruption-free setting using the professional’s choice in modeling software – GAMS. Domain experts will be teaching the following courses at locations worldwide:

June

September

Online Course

Essen, Germany

Introduction to Practical Global CGE Modeling with GAMS Prague, Czech Republic Practical General Equilibrium Modeling with GAMS Energy and Environmental CGE Modeling with GAMS Advanced Techniques in General Equilibrium Modeling with GAMS Overlapping Generation General Equilibrium Modeling with GAMS

August

Trade Policy Analysis with GAMS and MPSGE

November Weisenheim a.B., Germany Modeling and Optimization with GAMS (basic) Modeling and Optimization with GAMS (advanced)

Continuous Online Practical General Equilibrium Modeling with GAMS Online Advanced Techniques in General Equilibrium Modeling with GAMS

Annapolis, MD, USA Single Country General Equilibrium Modelling with GAMS and STAGE Global CGE Modelling with GAMS and GLOBE Frisco, CO, USA Basic GAMS Modeling – An Introductory Class Advanced GAMS Modeling

Take a look at our YouTube channel with instructional videos youtube.com/GAMSLessons

Further information and registration www.gams.com/courses