Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

TB31

4 - A Two-stage Design and Analysis of Computer Experiments Approach for Optimizing a System of Electric Vehicle Charging Stations Victoria C.P. Chen, The University of Texas at Arlington, Industrial, Manufacturing, & Systems Engr., Campus Box 19017, Arlington, TX, 76019-0017, United States, Ukesh Chawal, Jay Michael Rosenberger A two-stage framework is developed to address the design of a system of electric vehicle (EV) charging stations. The first stage specifies the design of the system that maximizes expected profit. Profit incorporates costs for building stations and revenue evaluated by solving a system control problem in the second stage. The control problem is formulated as an infinite horizon, continuous-state stochastic dynamic programming problem. To obtain a system design solution using our two-stage framework, we propose an approach based on design and analysis of computer experiments (DACE). 5 - Decision Analytic Framework for Evaluating Future Power Generation Pathways Power generation planning objectives are reliable power system, economic efficiency, environmental sustainability, and social acceptability. Multiple alternatives, consists of different technologies and resources, must be assessed in multiple objectives. The objective of this study is to develop a multicriteria decision analysis model to select a power generation pathway for Sri Lanka by developing different alternative pathways, examining them across multiple objectives, and incorporating preferences of multiple stakeholders. A pathway; mix of renewable and fossil fuel resources aimed at achieving energy security can meet multiple criteria associated with future power generation. Thushara De Silva, PhD Candidate, Vanderbilt University, 105 Jefferson Square, Nashville, TN, 37215, United States, George M. Hornberger, Hiba Baroud Chair: Tom Van Woensel, Eindhoven University of Technology, Industrial Engineering, Den Dolech 2, Pav F08, Mb Eindhoven, NL5600, Netherlands 1 - On Machine Learning and Discrete Optimization: Predicting Blurred Solutions for ILPs in Intermodal Container Loading Andrea Lodi, cole Polytechnique de Montr al, GERAD-HEC, 3000 Chemin de la Cote-Sainte-Catherine, Montr al, QC, H3T2A7, Canada In this talk, we advocate a tight integration of Machine Learning and Discrete Optimization (among others) to deal with the challenges of decision-making in Data Science. For such an integration, we briefly review possible directions and then we propose a methodology to predict descriptions of solutions to discrete stochastic optimization problems in very short computing time. We approximate the solutions based on supervised learning and the training dataset consists of a large number of deterministic problems that have been solved independently (and offline). Uncertainty regarding a subset of the inputs is addressed through sampling and aggregation methods. Our motivating application concerns booking decisions of intermodal containers on doublestack trains. Under perfect information, this is the so-called load planning problem and it can be formulated by means of integer linear programming. However, the formulation cannot be used for the application at hand because of the restricted computational budget and unknown container weights. The results show that standard deep learning algorithms allow to predict descriptions of solutions with high accuracy in very short time (milliseconds or less). A careful comparison with alternative stochastic programming approaches is provided. (Joint work with Eric Larsen, S bastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien.) Supply Chain Design and Operations I Sponsored: TSL/Freight Transportation & Logistics Sponsored Session Chair: Burcu B. Keskin, University of Alabama, Tuscaloosa, AL, 35406, United States 1 - Omni-channel Supply Chains with Unilateral Transshipments Emily Barbee, University of Alabama, Tuscaloosa, AL, 35487-0226, United States, Burcu B. Keskin Omni-channel supply chains integrate the brick-and-mortar and online sales channels of a company to achieve higher customer service and fill rates. Most n TB31 North Bldg 222A TSL Special Invited Speaker Sponsored: Transportation Science & Logistics Sponsored Session n TB32 North Bldg 222B

omni-channel supply chains facilitate unilateral transshipments to utilize in-store inventory to fulfill online demand. We quantify the impact of network design on inventory related costs and optimal order quantities. We maximize the profit of a newsvendor style problem and discuss concavity properties of the objective under different demand distributions. 2 - Transportation Planning in the Beverage Container Recycling Industry Robert Wiedmer, Arizona State University, Tempe, AZ, 85287, United States, Hakan Yildiz In many U.S. states, empty beverage containers are returned to retail stores from where they are picked up and transported to processing facilities. Stochastic demand in the beverage industry challenges efficient routing of pick-up vehicles. We analyze data from a logistics service provider and present methods to optimize pick-up operations. 3 - Strategic Network Design at the Polish Post Maciek A. Nowak, Loyola University Chicago, Information Systems and Supply Chain Mgmt, Quinlan School of Business, Solving the Service Network Design (SND) problem assists a freight transportation firm by prescribing the choice of paths for shipments and the services or resources necessary to execute them, while achieving the economic and service-quality targets of the carrier. This research extends a previously developed SND algorithm while incorporating data visualization to assist the Polish Post in creating a more efficient and effective network. 4 - The Strategic Value of Store Brands in a Common Retailer Channel Hongseok Jang, University of Florida, Gainesville, FL, United States, Quan Zheng, Xiajun Amy Pan In a common retailer channel with two asymmetric competing national brand manufacturers, we study whether the retailer should introduce a store brand. Our results reveal a continuum of boundary equilibria where the store brand with zero demand is offered so as to incentivize the manufacturers to lower the wholesale prices in a co-opetition manner. n TB33 North Bldg 222C Joint Session ORAM/QSR/Practice Curated: Panel Discussion on Academic Job Application and Interview Process Emerging Topic: OR and Advanced Manufacturing Emerging Topic Session Chair: Mohammed Shafae, University of Arizona, Tucson, AZ, 85743, United States 1 - Discussion on Academic Job Application and Interview Process Ahmed Aziz Ezzat, Texas A&M University, College Station, TX, United States Moderator for INFORMS annual meeting 2018 panel session entitled “Academic Job Application and Interview Process”. Panelists Janis Terpenny, Penn State University, Industrial & Manufacturing Engineering, 310 Leonard Building, University Park, PA, 16802, United States Elsayed A. Elsayed, Rutgers University, Department of Industrial and Systems Eng, 96 Frelinghuysen Road, Piscataway, NJ, 08854, United States Zhijian Pei, Professor, Texas A&M University, 101 Bizzell St., College Station, TX, 77843, United States Rachel Cummings, Georgia Tech, 755 Ferst Drive NW, Atlanta, GA, 30332-0205, United States Murat Yildirim, Wayne State University, 4815 Fourth Street, Detroit, MI, 48202, United States Mohammed Shafae, University of Arizona, Tucson, AZ, United States Chicago, IL, 60611, United States, Mike Hewitt, Bogumil Kaminski, Michal Pliszka, Rahul C. Basole

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