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Plenary Speakers

Michael A. Trick

Operations Research has had tremendous impact on companies and organizations over its 70+ year history. Recent advances in algorithms, computing, and data capture have created an environment where our field can be even more influential.  By combining predictive analytics, such as data mining and statistical approaches, with prescriptive analytics, such as optimization methods, our field can create systems that span multiple functions within an organization.  I will discuss the key trends that are affecting the world of operational research, and illustrate the impact of those trends in my own work in sports scheduling, telecommunication design and other application areas. 

Impacting Business by Combining Predictive and Prescriptive Analytics

Problems of optimization are concerned with making decisions "optimally". In many situations in management, finance and engineering, however, the decisions have to be made without knowing fully how they will play out in the future.  When the future is modeled probabilistically, this leads to stochastic optimization, but the formulation of objectives and constraints can be far from obvious.  

A future cost or hazard indicator may be a random variable which a present decision can influence only in shaping its distribution in a limited way.  For instance, it may be desirable to keep a hazard below a particular threshold, like building a bridge to resist earthquakes and floods, and yet it may be impossible or too expensive to guarantee that the threshold will never be breached. 

There needs to be a framework according to which the probability distribution a cost or hazard can be deemed "adequately" below the desired threshold.  That is the role for so-called "measures of risk," which
started to be developed for purposes like assessing the solvency of banks but now are being utilized much more widely.  Measures of risk also offer fresh ways of dealing with reliability constraints, such as have traditionally been imposed in engineering in terms of bounds on the probability of failure of various manufactured components.  Probability of failure has troublesome mathematical behavior in an optimization
environment.  Now, though, there is a substitute, called buffered probability of failure, which makes better sense and is much easier to work with computationally.

Harold Larnder Memorial Lecture - Terry Rockafellar

Ralph Tyrrell (Terry) Rockafellar has long been associated with the the University of Washington, Seattle, where he is Professor Emeritus of Mathematics.  However, he has also contributed in recent years as Adjunct Research Professor of Systems and Industrial Engineering at the University of Florida, Gainesville, and as Honorary Professor of the Department of Applied Mathematics at Hong Kong Polytechnic University.  

His interests span from convex and variational analysis to problems of optimization and equilibrium, especially nowadays applications in finance, engineering and economics involving risk and reliability, along with schemes of problem decomposition in convex and nonconvex programming. 

 

In addition to being a winner of the Dantzig Prize given jointly by SIAM and the Mathematical Programming Society (1983), Prof. Rockafellar has gained international recognition for his work through honorary doctorates bestowed by universities in a number of countries.  INFORMS awarded him and Roger Wets the 1997 Lancaster Prize for their book Variational Analysis, and in 1999 he was further honored by INFORMS with John von Neumann Theory Prize for his fundamental contributions to the methodology of optimization. He has authored over 250 publications, including one of the all-time most highly cited books in mathematics, Convex Analysis.

Risk and Reliability in Optimization Under Uncertainty

Operations Research has had tremendous impact on companies and organizations over its 70+ year history. Recent advances in algorithms, computing, and data capture have created an environment where our field can be even more influential.  By combining predictive analytics, such as data mining and statistical approaches, with prescriptive analytics, such as optimization methods, our field can create systems that span multiple functions within an organization.  I will discuss the key trends that are affecting the world of operational research, and illustrate the impact of those trends in my own work in sports scheduling, telecommunication design and other application areas.  

Michael Trick

Michael Trick is Dean of Carnegie Mellon University in Qatar and is the Harry B. and James H. Higgins Professor of Operations Research at the Tepper School of Business, CMU.  He is a researcher and educator in the field of operations research, with a specialization in computational methods in optimization.  He received his undergraduate degree in combinatorics and optimization from the University of Waterloo and his doctorate in industrial engineering from Georgia Tech. He joined Carnegie Mellon University in 1989.  He has served as President of INFORMS and as President of the International Federation of Operational Research Societies.  Dr. Trick is the author of more than fifty professional publications and is the editor of six volumes of refereed articles.  Trick has consulted extensively with the United States Postal Service on supply chain design, with Major League Baseball and a number of college basketball conferences on scheduling issues, and with the Federal Communications Commission on bandwidth allocation.

Impacting Business by Combining Predictive and Prescriptive Analytics

Policy Modeling refers to the application of operations research, statistics, and other quantitative methods to model policy problems. Recognizing that analyses of all sorts often exhibit diminishing returns in insight to effort, the hope is to capture key features of various policy issues with relatively simple "first-strike" models. Problem selection and formulation thus compete with the mathematics of solution methods in determining successful applications.  I will review some personal adventures in policy modeling selected from public housing, HIV/AIDS prevention, bioterror preparedness, counterterrorism, and immigration policy.

Edward H. Kaplan

Edward H. Kaplan is the William N. and Marie A. Beach Professor of Operations Research, Public Health, and Engineering at Yale University’s School of Management. Kaplan is a graduate of Greystone Heights Elementary School and Evan Hardy Collegiate Institute, both in Saskatoon.  He received his Bachelor’s Degree from McGill University in 1977 with First Class Honours, three Masters degrees from MIT (1979 in operations research, 1979 in city planning, and 1982 in mathematics), in addition to his MIT PhD in 1984.  He joined the Yale faculty in 1987 following appointments at Harvard’s Kennedy School and the University of Massachusetts-Boston.  An expert in operations research, mathematical modeling and statistics, Kaplan has co-authored more than 140 academic papers.  He was elected to the US National Academy of Engineering and the Institute of Medicine (now the National Academy of Medicine), and is an Institute of Operations Research and the Management Sciences (INFORMS) Fellow. His research in HIV prevention and counterterrorism has been recognized with the Edelman Award, Lanchester Prize, Centers for Disease Control’s Charles C. Shepard Science Award, INFORMS President’s Award, the Philip McCord Morse Lectureship, three Koopman Prizes, and numerous other awards. Kaplan was the Lady Davis Visiting Professor of medicine and of statistics at the Hebrew University of Jerusalem, and also served as a visiting professor to the Faculty of Industrial Engineering and Management at the Technion-Israel Institute of Technology, the Survey Research Center at UC Berkeley, Columbia’s Graduate School of Business, MIT’s Sloan School of Management, and Stanford’s Graduate School of Business.  For more information about Kaplan and his research, visit http://faculty.som.yale.edu/EdKaplan/.

Adventures in Policy Modeling!

The operations research problems in the healthcare industry are generally very similar to corresponding problems in any other sector. Hospitals have staffing issues, budget constraints, purchasing decisions, scheduling, planning, etc.  The differences are subtle and often related to the culture. Over the years, I have encountered many challenges and I have been able to design approaches to deal with many of them. A few years ago, I was asked to pick the five top challenges. I can easily rattle off 30, but selecting five was itself a challenge. In this talk, I will outline my perception of the major hurdles, provide a few examples and discuss some strategies for overcoming them.

Canadian Healthcare Optimization Workshop - Keynote Speaker

Michael Carter is a Professor in the Department of Mechanical and Industrial Engineering at the University of Toronto (since 1981) and Founding Director of the Centre for Healthcare Engineering (in 2009). Since 1989, his research focus has been in the area of health care resource modeling. As of May 2019, Mike has supervised 26 Ph.D. students and 94 Masters and directed more than 280 undergraduate engineering students in over 130 projects with industry partners. He is cross appointed to the Institute of Health Policy, Management and Evaluation and the School of Public Policy & Governance at Toronto. He was the winner of the Annual Practice Prize from the Canadian Operational Research Society (CORS) four times (1988, 1992, 1996 and 2009). In 2000, he received the CORS Award of Merit for lifetime contributions to Canadian Operational Research. He is on the editorial board for the journals “Health Care Management Science”, “Operations Research for Health Care”, “Health Systems” and “IIE Transactions on Healthcare Systems”. He is an Adjunct Scientist with the Institute for Clinical Evaluative Sciences in Toronto (www.ices.on.ca) and a member of the Faculty Advisory Council for the University of Toronto Chapter of the Institute for Healthcare Improvement (IHI). He is member of the Professional Engineers of Ontario.  In 2012, he was inducted as a Fellow of the Canadian Academy of Engineering and in 2013, he was inducted as a Fellow of INFORMS, the international society for Operations Research and Management Science. In 2018, he became a Fellow of the Canadian Academy of Health Sciences. In 2019, he won the Northrup Frye Award for Teaching Excellence from th U of Toronto Alumni Association.

Top five challenges of modelling in healthcare