Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

WB35

5 - The Time Dependent Vehicle Routing Problem with Time Windows and Real Traffic Penalties Benchmark Problems and a Simulated Annealing Heuristic Shin-Yu Lin, Metropia, Tucson, AZ, 85719, United States National Taiwan University of Science and Technology, 43, Section 4, Keelung Road, Taipei, 10607, Taiwan, Yi-Chang Chiu, Vincent F. Yu, Ali Arian In this study, the time dependent vehicle routing problem with time windows and real traffic penalties (TDVRPTW-RTP), a variant of vehicle routing problem (VRP) when considering time dependent travel times, time windows demands, and traffic behavior, is introduced and formulated. A new dataset is created by modifying Solomon dataset and is solved by our proposed simulated annealing heuristic (SA) and multi-start SA (MSA). This study collects time dependent travel time with traffic penalties data and apply our proposed heuristic to a real world application in Taipei, Taiwan. The best solutions during the sensitivity analysis are used as benchmarks for further research comparing. 6 - Vehicle Routing Problem with Markov Decision Process Jihyun Jo, Pennsylvania State University, 234 Leonhard Building, University Park, PA, 16802, United States Static delivery vehicle routing problem is difficult to apply in urban transportation network due to the several reasons. For example, traffic conditions are changed dynamically. In addition, it is difficult to adapt the other path options. To handle these problems, we consider Markov decision process model. The objective of the model is finding optimal action at a given network condition. Optimal action contains the next location to visit as well as path option that agent will take. We assume fully observable stochastic network conditions when the agent make a decision. In this presentation, we define the mathematical model and introduce simple approximate method. Game Theory I Contributed Session Chair: Xicheng Yin, Tongji University, 1239 Siping Road, Shanghai, P.R., China 1 - Design of Third Party Intervention Strategy in the Conflict Haiyan Xu, Nanjing University of Aeronautics and Astronautics, 23 Avenue Guy de Collongue, Nanjing, 69130, China This research aims to provide the intervention strategy for the third party to mediate the conflict between two decision makers. The intervention strategy is designed to minimize the adjustments of preferences of the two DMs to make them achieve an equilibrium easily based on the graph model for conflict resolution. Therefore, an integer program is constructed with the constrains based on the requests. The solutions of this model can assist the third party to guide DMs to be stable for a given state. 2 - Compensation Regulation and Morel Hazard in Banking Minglong Zhou, NUS, 1 Business Link, Singapore, Jussi Keppo We model banking industry as a three stage asymmetric game between regulators, banks, and bankers. The regulators affect banks and bankers’ incentives by using different compensation regulations. We identify conditions under which different compensation regulations are effective. Our results also explain observed behavior in the industry. 3 - Online Privacy and Information Disclosure by Consumers Shota Ichihashi, Stanford University, 579 Serra Mall, Stanford, CA, 95051, United States I study the welfare and price implications of consumer privacy. A consumer discloses information to a multi-product firm, which learns about his preferences, sets prices, and makes product recommendations. While the consumer benefits from accurate product recommendations, the firm may use the information to price discriminate. I show that the firm prefers to commit to not price discriminate to encourage information disclosure. However, this commitment hurts the consumer, who could be better off by precommitting to withhold some information. In contrast to single-product models, equilibrium is typically inefficient even if the consumer can disclose any information about his preferences. 4 - Prospect Games and Regulated Prospect Games: Modeling Adversarial Inducement Brian J. Lunday, Air Force Institute of Technology, 2950 Hobson Way, Wright Patterson Air Force Base, OH, 45433, United States, William Caballero, Richard F. Deckro Populations are often confronted with multiple entities simultaneously attempting to influence their actions. Herein, we describe two new game theoretic frameworks, denoted as prospect games and regulated prospect games, that respectively model (a) the interactions of competing persuaders affecting a n WB34 North Bldg 223

populace and (b) the actions of a regulating agent to alter such a framework, and illustrate civil applications thereof. We provide a modeling framework for competitive persuasion operations, develop model variants that respectively correspond to scenario-specific modifications, and identify and selectively illustrate practical solution methods for the suite of models. 5 - Agent-based Opinion Formation Modeling in Social Network: A Perspective of Social Psychology and Evolutionary Game Theory Xicheng Yin, PhD Student, Tongji University, Shanghai, 200092, China, Hongwei Wang, Pei Yin We propose an agent-based online opinion formation model based on attitude change theory, group behavior theory and evolutionary game theory in the perspective of sociology and psychology. Three factors influence the persuasion process, including credibility of the leaders, characteristic of the recipient, and group environment. The model is applied to Twitter to analyze the influence of topic type, parameter changing, and opinion leaders on opinion formation. Results show that controversial topic shows greater uncertainty and sustainability. The ratio of benefit to cost has a significant impact on opinion formation. Celebrities are more capable of influencing public opinion than experts. n WB35 North Bldg 224A Hub and Air Cargo Operations Sponsored: Aviation Applications Sponsored Session Chair: Farshid Azadian, Embry-Riddle University, College of Business, Daytona Beach, FL, 32114, United States 1 - A Sustainable-resilient Network Design for Indian Aviation Sector Suresh Kumar Jakhar, Indian Institute of Management Lucknow, IIM Lucknow Campus, Lucknow, 226013, India We propose a capacitated multiple allocation p-median hub location problem. The multiple objective functions consider economic, environmental, and social performance goals. We deal with inherent uncertainty in parameters by using mean absolute deviation and fuzzy possibilistic-stochastic programming. The proposed formulation is used in a case study of Indian aviation industry. 2 - Comparing the Fixed and Flexible Hub Assignment Approaches When Solving the Express Shipment Service Network Design Problem When solving the Express Shipment Service Network Design (ESSND) problem, most models from the literature assume that the assignment of packages to hubs is fixed. However, there are no methods in the literature to determine such hub assignments. We first develop an exact model that integrates the hub assignment decisions into the ESSND problem. Then, we develop 4 heuristic methods to determine the hub assignments for the fix hub assignment approach. Finally, we compare the fix and flexible hub assignment approaches with realistic instances, showing clear advantages for the flexible approach. 3 - Unpaired Pickup and Delivery Problem with Time Dependent Assignment Costs Farshid Azadian, Associate Professor, Embry-Riddle University, Daytona Beach, FL, 32114, United States This study considers a freight forwarder’s operational implementation of alternative access airport policy in a multi-airport region for cargo transportation. Given a set of heterogeneous air cargo customers, the forwarder’s problem is to simultaneously select air cargo flight itineraries and schedule the pickup and delivery of customer loads to the airport(s). This problem is formulated as a novel pickup and delivery problem, where the delivery cost is both destination and time dependent. A mixed-integer linear model in presented and an efficient solution method based on decomposition is developed. The performance of the solution algorithm is evaluated by computational experimental study. Jose Miguel Quesada, Universit catholique de Louvain, Av Moliere 325, Uccle, 1180, Belgium, Jean-Charles Lange, Jean-Sebastien Tancrez

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