IEMS Research and Vision on Display at the INFORMS 2020 Annual Meeting

       The Institute for Operations Research and the Management Sciences (INFORMS) is the foremost professional society in its field, operating numerous journals,  specialized societies, student organizations, and annual awards that are among the most prestigious in its sphere.  Much of this activity comes to a head at the INFORMS Annual Meeting, with a host of speaking, networking, and recognition events that draw participants from around the globe. This year’s meeting, held November 8th through 13th, featured a typically strong contingent from Northwestern’s Department of IEMS, with multiple highlights throughout the week.

       Presentations of original research are at the heart of the agenda, but two IEMS speakers went further, addressing key future directions of the field.  Professor Barry Nelson’s keynote, “Rebooting Simulation for Big Data, Big Computing and Big Consequences,” discussed the origins and evolution of simulation research in the context of decades of remarkable advances in computing power.  With advances in machine learning, data storage, and parallel computing allowing for higher fidelity models, Professor Nelson gave a vision for how research in stochastic simulation should adapt. 

       In his TutORial session, “Diversity, Equity, and Inclusion in Operations Research and Analytics: A Research Agenda for Scholarship, Practice, and Service”, Professor Michael Johnson (IEMS PhD ’97) highlighted how an active reimagining could transform the larger discipline.  Professor Johnson remarked that, as one example, INFORMS’ demographics lag the diversity of our society.  Professor Johnson demonstrated how DEI principles applied to OR projects could better reflect all stakeholders.  Professor Johnson, Chair of the Department of Public Policy and Public Affairs at the University of Massachusetts Boston, led further discussion with IEMS in a November 17th department seminar [link].

       Alongside its role as a forum for new ideas, the Annual Meeting recognizes outstanding achievement and leadership. The INFORMS Chapters/Fora Committee bestowed its Magna Cum Laude honor on the Northwestern chapter, recognizing it as one of the most effective student chapters in 2020.  Daniel Duque (IEMS PhD ’20), alongside collaborator Remy Pasco of the University of Texas at Austin, won second prize in the Doing Good with Good OR competition for their paper “COVID-19: How to Relax Social Distancing If You Must.”  Yue Hu (IEMS BSIE '17) won the Applied Probability Society Best Paper Award for "Asymptotic Optimality of the Binomial-Exhaustive Policy for Polling Systems with Large Switchover Times", written with IEMS Professor Ohad Perry and Professor Jing Dong of Columbia University during her PhD work at that institution.  Professor Karen Smilowitz was named Editor-in-Chief of the prestigious journal, Transportation Science [link]. Professor Smilowitz and Professor Samantha Meyer Keppler (IEMS PhD ‘15) also gave a TutORial, “On the use of Operations Research and Management in Public Education Systems.”

        The pace of IEMS research has not slowed amid COVID-19.  In all, 13 PhD students, 6 faculty members, 2 postdocs, and 9 recent members of the department presented throughout the conference, with a number of additional alumni represented throughout the schedule as well. A list of IEMS presentations follows:

 

Presenter Title
Harun Avci Improving The Performance Of Complete Expected Improvement In Stochastic Simulation Optimization
Pol Boada-Collado

Demand Visibility And Capacity Pooling With Temporal Commitments

Estimation Of Customers Preferences In Attended Home Delivery

Daniel Duque COVID-19: How to Relax Social Distancing if you Must
David J. Eckman Using Functional Properties To Screen Out Simulated Solutions In Large Decision Spaces
Mariana Escallon Volunteer Scheduling Networks: An Application To The Red Cross Disaster Response Program
Eojin Han Designing Interpretable Policies In Distributionally Robust Optimization
Niloufar Izadinia Optimization-based Metrics Of Multilevel Performance In Multiteam Systems
Gokce Kahvecioglu Finding All Pareto Optimal Solutions To A Graph Clustering Problem
Simge Kucukyavuz A Consistent Second-order Conic Integer Programming Approach For Learning Bayesian Networks
Dabeen Lee Improved Formulations For Distributionally Robust Chance-constrained Programs Under Wasserstein Ambiguity
Jacob Mays Missing Incentives for Flexibility in Wholesale Electricity Markets
Sanjay Mehrotra A Method for Solving Convex-Concave Fractional Programs using Second Order Cones, with an Application to Equitable Resource Allocation
Barry L. Nelson Rebooting Simulation for Big Data, Big Computing and Big Consequences
Reut Noham Designing Operation Policies For Early Intervention: Improving Therapy Services For Children With Disabilities
Bernardo K. Pagnoncelli On Solving Multistage Stochastic Programs With The Entropic Risk Measure
Hamed Rahimian Multi-product Newsvendor Problem With Decision-dependent Demand
Chang-Han Rhee Heavy-tailed Phenomena In Systems With Light-tailed Components
Simon Risanger The Impact Of Financial Transmission Rights On Generation Investments
Mark Semelhago Rapid Gaussian Markov Improvement Algorithm For Discrete Simulation Optimization
Hao-Jun M. Shi A Noise-tolerant Quasi-Newton Method For Unconstrained Optimization
Karen Smilowitz On The Use Of Operations Research And Management In Public Education Systems
Zhe Su Stochastic Gradient Descent and Sample Path Large Deviations for Heavy-Tailed Levy Processes in Multiple Dimensions
Andreas Waechter An Active-Set Method For Second-Order Cone Programming
Xingyu Wang Efficient Rare-event Simulation For Multiple Jump Events Of Heavy-tailed Levy Processes With Infinite Activities
Linchuan Wei On The Convexificaiton Of Constrained Nonlinear Optimization Problem With Indicator Variables
Eugene Wickett Inferring Sources Of Dangerous Products In Pharmaceutical Supply Chains
Yuchen Xie Theory Of The BFGS Method For Noisy Problems: Adaptive Lengthening, Linesearch And Convergence Analysis
Haoxiang Yang

Two-stage Stochastic Mixed-Integer Programming Approach to Integrate Protection and Restoration Planning

Distribution Network Optimization under Stochastic Disruptions

Lun Yu Optimal Clearing Of Backlogs In Multi-class Queueing Systems
Qimeng (Kim) Yu A Polyhedral Approach To Bisubmodular Function Minimization

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