2016 INFORMS Annual Meeting Program

TC89

INFORMS Nashville – 2016

TC90 Broadway D-Omni Logistics, Humanitarian Contributed Session Chair: Behnam Malmir, Kansas State University, 2034 Durland Hall, 1701A Platt street, Manhattan, KS, 66506, United States, malmir@ksu.edu 1 - Human Trafficking: Opportunities For Operations Research And Management Science Renata Alexandra Konrad, Worcester Polytechnic Institute, School of Business, 100 Institute Road, Worcester, MA, 01609, United States, rkonrad@wpi.edu This talk highlights how OR/MS techniques can be used to address the growing issue of human trafficking. We provide insights into the unique challenges and opportunities for the OR/MS community and suggest development areas. We present a case study of victim shelter location in Nepal and share our experiences in working in this field. 2 - Pre-disaster Unmanned Air Vehicle Base Location & Routing For Road Damage Assessment & Search & Rescue Seyyed kian Farajkhah, Cankaya-Middle East Technical University, Universiteler, Dumlupinar, Bulvari No1, Ankara, 06800, Turkey, kian.farajkhah@metu.edu.tr we consider the problem of locating UAV bases in anticipation of alarge-scale disaster in an urban environment.We propose a two-stage stochastic programming approach for this problem, where first-stage decisions consist of base locations and UAV routes, and the second-stage is comprised of assigning these ambulances to different demand point and hospitals. Using small-sized instances, we aim to analyze the structure of the optimal solutions and use the results of this analysis to develop a heuristic approach for larger instances. 3 - Impact Of Patient Centered Discharge On Quality Of Life And Readmission Rates For Kidney Transplant Recipients Aravind Chandrasekaran, The Ohio State University, 600 Fisher Hall, 2100 Neil Avenue, Columbus, OH, 43210, United States, chandrasekaran.24@osu.edu, Luv Sharma, Gopesh Anand This study looks at the impact of a patient centered discharge process in improving the quality of life and readmission rates for kidney transplant recipients. This three year study was conducted at a large teaching hospital in the Midwest and involved designing and implementing a new patient centered discharge process with inputs from patients and caregivers. Initial results demonstrate a 15% reduction in readmission rates post implementation of the new discharge process. A comparable improvement in readmission rate is also observed when compared to a control group comprised of other types of transplant patients. SIMIO/Neusrel Technology Tutorial 1 - New Innovations: Cloud Computing, Real-Time Scheduling, Healthcare, And More Claude Dennis Pegden, CE/Founder, Simio LLC, Sewickly, PA, United States, cdpegden@simio.com, Renee Thiesing Simio now leverages the cloud computing power of Microsoft Azure to support your most demanding applications; compatibility with Schneider Electric’s Wonderware to allow detailed production scheduling with real-time data and risk analysis; and healthcare and other capabilities in the services field. Outside our immense technology partner advances, we have great new features, application areas and capabilities! Come explore an overview of the new Simio experience and see why we are always “Forward Thinking.” 2 - NEUSREL - Success Drivers David Buckler, Neusrel, Chantilly, VA, United States, dbuckler@caci.com NEUSREL is self-learning causal analysis software and leverages Advanced Machine Learning techniques. It builds cause-effect networks (path models) in order to understand the impact and role of success factors. The software is the only solution worldwide that is able to explore unexpected nonlinearities and unexpected interactions - a capability that not only lead to largely increased explanation power but turned out to be crucial when understanding true key drivers of outcomes. The software is applied in all fields were many factors drives a particular outcome and therefore it is not clear how important those are and how they interact. TC94 5th Avenue Lobby-MCC

5 - On The Benefit (or Cost) Of Large-scale Bundling Tarek Abdallah, New York University, tabdalla@stern.nyu.edu We study the effectiveness of a simple bundling mechanism in extracting the consumer surplus in the presence of non-negative marginal costs and correlated valuations. We develop simple robust analytics that identify the main drivers for the effectiveness of the pure bundling mechanism and allow the sellers to easily quantify the potential profits of a large-scale bundling mechanism relative to more complicated selling mechanisms. Our numerical simulations show that these analytics provide high predictive power for the true performance of the bundling mechanism and are robust to different parametric assumptions even for relatively small bundles. TC89 Broadway C-Omni Applications of Optimization and Control Theory in Traffic Management Sponsored: TSL, Intelligent Transportation Systems (ITS) Sponsored Session Chair: Xiaozhang He, Purdue University, 1, West Lafayette, IN, 47906, United States, seanhe@purdue.edu 1 - On The Equity Issue Of Taxi Market Under A Centralized Recommendation System Xinwu Qian, Purdue University, West Lafayette, IN, United States, qian39@purdue.edu, Xianyuan Zhan, Sattish Ukkusuri The lack of perfect information between passengers and drivers is the main cause of the taxi system inefficiency, and having a centralized recommendation system will effectively address this inefficiency. In this study, we model the taxi market with centralized recommendation system, with the objective to minimize the income differences among taxi drivers. The model aims to address the equity issue related to income variance, which helps to improve the stability of the taxi market. We first prove that the problem is NP-hard, and we propose a meta- heuristic algorithm to solve the large-scale real world case efficiently. 2 - Feedback-based Traffic Signal Perimeter Control For Urban Networks Under special Traffic Events Jiawen Wang, Tongji University, School of Transportation Engineering, Shanghai, China, 07wangjiawen@tongji.edu.cn, Xiaoguang Yang, Xiaozheng He, Srinivas Peeta This study develops a proportional-integral-derivative controller for traffic signal perimeter control to maximize the throughput of urban networks under special traffic events. The proposed control strategy applies the notion of macroscopic fundamental diagram to dynamically estimate the control targets. Numerical examples are constructed to investigate the benefits of the proposed control strategy in improving the traffic mobility when special traffic events occur. 3 - Simulation-based Optimization With AdaptiveSampling Strategy For Network-wide Traffic Management And Control Shubham Agrawal, Purdue University, West Lafayette, IN, 47907, United States, shubham@purdue.edu, Xiaozheng He, Ragu Pasupathy, Srinivas Peeta This study develops a simulation-based optimization model to address network- wide traffic management and control problems under a tight computational budget by applying an adaptive sampling strategy. The proposed model is suitable to solve traffic management and control problems, which can determine traffic signal timing, route guidance, and ramp metering simultaneously. Numerical results are used to illustrate the efficiency of the adaptive sampling strategy in enhancing the performance and reliability of traffic management and control systems in operational context.

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