INFORMS 2021 Program Book

INFORMS Anaheim 2021

TD02

Tuesday Keynote 04 CC Ballroom D /Virtual Theater 4 2021 Wagner Prize Winner Reprise Keynote Session

Tuesday, 1:30PM-2:30PM

Tuesday Keynote 01 CC Ballroom A /Virtual Theater 1 Keynote: Policy Modeling for SARS-CoV-2 Screening, Prevention, and Vaccination Keynote Session 1 - Policy Modeling for SARS-CoV-2 Screening, Prevention, and Vaccination A. David Paltiel, Professor, Yale School of Public Health, Dept of Epidemiology & Pub Health, New Haven, CT, 06520-8034, United States In 2020, the SARS-CoV-2 pandemic repeatedly forced decision makers to confront the tradeoff between clinical, epidemiological, and economic considerations. More often than not, a policy response was demanded long before major uncertainties could be resolved via the traditional forms of health and medical investigation. I will present four dilemmas, each of which was the topic of front-page media coverage, and describe my personal experiences developing simple policy models to address them: How to reopen college campuses safely? How to trade vaccine efficacy against speed of implementation? How to choose between single- and two-dose vaccines? How to evaluate the costs and benefits of population-wide, home-based, rapid, antigen testing? Tuesday Keynote 02 CC Ballroom E /Virtual Theater 2 Keynote: Lagrangian Control at Large and Local Scales in Mixed Autonomy Traffic Flow Keynote Session 1 - Lagrangian Control at Large and Local Scales in Mixed Autonomy Traffic Flow Alexandre Bayen, University of California-Berkeley, Berkeley, CA, United States This talk investigates Lagrangian (mobile) control of traffic flow at local scale (vehicular level). The question of how will self-driving vehicles will change traffic flow patterns is investigated. We describe approaches based on deep reinforcement learning presented in the context of enabling mixed-autonomy mobility. The talk explores the gradual and complex integration of automated vehicles into the existing traffic system. We present the potential impact of a small fraction of automated vehicles on low-level traffic flow dynamics, using novel techniques in model-free deep reinforcement learning, in which the automated vehicles act as mobile (Lagrangian) controllers to traffic flow. Illustrative examples will be presented in the context of a new open-source computational platform called FLOW, which integrates state of the art microsimulation tools with deep-RL libraries on AWS EC2. Interesting behavior of mixed autonomy traffic will be revealed in the context of emergent behavior of traffic: https://flow- project.github.io/ Tuesday Keynote 03 CC Ballroom C /Virtual Theater 3 IFORS Distinguished Lecture Keynote Session 1 - Using OR to Improve Emergency Vehicle Planning and Performance Karen Aardal, Delft University of Technology, TU Delft, Mekelweg 4, Delft, 2628 CD, Netherlands In life-threatening situations each second counts. It is therefore of utmost importance that emergency medical response vehicles are used efficiently. This involves determining ambulance location sites, and the number of vehicles that should be stationed at these sites, as well as using dispatch policies that keep sufficient coverage even when a subset of vehicles are dispatched to calls. In this talk we will review emergency medical response vehicle location models and dispatch algorithms with a focus on road ambulances and helicopters. The main body of the work presented here is an outcome of research projects involving university researchers in the Netherlands and Norway, and representatives from the National Institute for Public Health and the Environment in the Netherlands, the Norwegian Air Ambulance Foundation, and regional Health Trusts.

The Daniel H. Wagner Prize is awarded for a paper and presentation that describe a real-world, successful application of operations research or advanced analytics. The prize criteria emphasizes innovative, elegant mathematical modeling and clear exposition.

Tuesday Keynote 05 CC Ballroom E / Virtual Theater 2 Keynote: 2021 UPS George D. Smith Winner Reprise Keynote Session 1 - University of Iowa, Department of Business Analytics Ann Melissa Campbell, University of Iowa, Iowa City, IA, 52242- 1994, United States 2021 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. INFORMS, with the help of the INFORMS Practice Section, will award the prize to an academic department or program for effective and innovative preparation of students to be good practitioners of operations research, management science, or analytics.” The UPS George D. Smith Prize is named in honor of the late UPS Chief Executive Officer who was a champion of operations researchers at a leading Fortune 500 corporation. UPS generously sponsors the award in his memory.2021The 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. INFORMS, with the help of the INFORMS Practice Section, will award the prize to an academic department or program for effective and innovative preparation of students to be good practitioners of operations research, management science, or analytics. The UPS George D. Smith Prize is named in honor of the late UPS Chief Executive Officer who was a champion of operations researchers at a leading Fortune 500 corporation. UPS generously sponsors the award in his memory. TD02 CC Ballroom B / Virtual Theater 2 Hybrid Location Models I Sponsored: Location Analysis Sponsored Session Chair: Zvi Drezner, California State University Fullerton, Fullerton, CA, 92834, United States Co-Chair: Pawel J. Kalczynski, California State University-Fullerton, Fullerton, CA, 92834-6848, United States 1 - A Sinkhorn Algorithm for the Quadratic Assignment Problem Samhita Vadrevu, UIUC, University of Illinois at Urbana- Champaign, Champaign, IL, 61801, United States, Rakesh Nagi A Sinkhorn based approach is proposed to solve the Quadratic Assignment Problem. Linear programs of the lifted formulations of QAP are considered formulated as an Optimal Transport Problem. By applying iterative projections, an approximate solution is found for the LP. A GPU accelerated algorithm is designed to find these approximate solutions and then a GPU based Branch and Bound technique is used to find integral solutions to QAP, thus achieving an accurate solution via an efficient and scalable algorithm. 2 - Optimal Placement of M Finite-size Rectangular Facilities in an Existing Layout: Exact Solution Methods, Lower Bounds, and Heuristics Rakesh Nagi, U. of Illinois at Urbana-Champaign, Department Of Industrial Enterprise Systems Transp, Urbana, IL, 61801, United States, Ketan Date In this paper we investigate a new problem of optimal placement of M finite-size rectangular facilities in presence of existing rectangular facilities. To find a solution, we divide the feasible region into sub-regions and prove that the candidates for the optimal placement of the new facilities can be drawn from the boundary of these sub-regions. We design a branch-and-bound algorithm suitable for navigating this highly degenerate search space. Heuristic procedures perform well for non-pathological cases with an acceptable optimality gap. Our Tuesday, 2:45PM 4:15PM

125