2015 Informs Annual Meeting

WB71

INFORMS Philadelphia – 2015

WB69 69-Room 201C, CC ITS in Public Transportation Sponsor: TSL/Intelligent Transportation Systems (ITS) Sponsored Session Co-Chair: Alireza Khani, Assistant Professor, University of Minnesota, United States of America, akhani@umn.edu 1 - Vehicle-Sharing Network Design and its Integration with Public Transportation Services Tianli Zhou, Massachusetts Institute of Technology, Cambridge, MA, United States of America, tzhou90@mit.edu, Virot Chiraphadhanakul, Cynthia Barnhart, Carolina Osorio We consider the design of a one-way vehicle sharing (VS) system, such that it is complementary with an existing public transportation system. We propose a two- stage MIP formulation to address a VS network design problem. We consider a large-scale case study of the metropolitan area of Boston. To solve the model, we decompose it and develop a cut generation method. We present numerical results for the Boston case study. 2 - A Location and Scheduling Model for a Flexible Intercity Transit Service Andisheh Ranjbari, University of Arizona, Tuscon, AZ, United States of America, aranjbari@email.arizona.edu, Mark Hickman, Yi-Chang Chiu ”Flexpress” is a high-speed intercity bus transit service that has several terminal locations in the urban area and a dynamic schedule. Travelers have the choice to board/alight the vehicle at one of the designated terminals, or pay a premium cost and ask for a door-to-door service. This presentation focuses on the mathematical model for the terminal location and scheduling problems. 3 - Transit Passenger Flow Prediction under Event Occurrences with Social Media Data Ming Ni, SUNY Buffalo, 326 Bell Hall, University at Buffalo, Amherst, NY, 14260, United States of America, mingni@buffalo.edu, Jing Gao, Qing He Frist, we propose a hashtag-based method to identify events near NYC subway stations based on tweets data. Second, the relationship between social activities and subway passenger flow is unveiled. Third, a convex optimization based model is developed to predict subway volume with social media data. 4 - Reliable Routing in Schedule-based Transit Networks with Stochastic Travel Times Alireza Khani, Assistant Professor, University of Minnesota, United States of America, akhani@umn.edu, Stephen Boyles In schedule-based transit networks where service is time-dependent and stochastic, risk-averse users try to minimize the expected travel time as well as to maximize the chance of arriving on-time. The latter objective is modeled by transfer failure probability and path algorithms are developed to find the most reliable paths. WB70 70-Room 202A, CC Vehicle Routing I Contributed Session Chair: Sadegh Mirshekarian, PhD Student, Ohio University, 285 Stocker Center, Athens, OH, 45701, United States of America, sm774113@ohio.edu 1 - Branch-and-cut Algorithms for the Time Constrained Covering Salesman Problem Gizem Ozbaygin, PhD Candidate, Bilkent University, Department of Industrial Engineering, Ankara, Turkey, ozbaygin@bilkent.edu.tr, Hande Yaman, Oya E. Karasan In this study, we consider the time constrained maximal covering salesman problem which is a generalization of the orienteering problem. We propose a mathematical formulation, valid inequalities and branch-and-cut algorithms for the problem. We test our approaches on several instances we generated based on some existing VRP instances and report the results of our computational study.

2 - A Fuzzy Vehicle Routing Problem with Time Windows under Driving and Working Time Restrictions

Can Celikbilek, Ohio University, Industrial & Systems Engineering, Athens, OH, United States of America, cc340609@ohio.edu, Gursel Suer

A new Fuzzy mathematical model is developed to maximize the total profit of the system while minimizing the total traveled distance. The developed mathematical model is tested considering real driving, service and working time restrictions. A single depot and multiple customers with their working time windows are considered with identical set of vehicles. The developed fuzzy mixed integer mathematical model provided promising solutions to provide insights to real industry problem. 3 - Time Dependent Vehicle Routing Problem Solving Based on Speed Profiles and Speed Drop Coefficients Martina Ravlic, Faculty of Transport and Traffic Sciences, University of Zagreb, Vukeliceva 4, Zagreb, Croatia, mravlic@fpz.hr, Tomislav Erdelic, Tonci Caric The vehicle routing problem in real cases can be solved by applying a TDVRP algorithm. We compared two existing methods for determining the minimum travel time in TDVRP algorithm: the first method uses speed profiles of traversed links, while the other uses speed drop coefficients on a wider road network area. We analyzed the relationship between the execution times, depending on the size of the problem, and the computed minimum travel times with measured times. 4 - A Vehicle Routing Problem with Budget and Time Constraints Elham Kookhahi, Wichita State University, 1845 Fairmount Street, Wichita, KS, 67260, United States of America, exkookhahi@wichita.edu, Bayram Yildirim In this paper, a mathematical model is presented for a vehicle routing problem in which a sub tour of cities can be visited to maximize the number of served customers with a limited budget and time. The problem is solved using a genetic algorithm and numerical results are presented. 5 - A Generalized Single-Depot Vehicle Routing Problem with Time Windows and Non-Identical Vehicles Sadegh Mirshekarian, PhD Student, Ohio University, 285 Stocker A generalized variant of VRP with time windows is studied, considering vehicles different in capacity, cost and speed. Vehicles can be used for more than one route, but are subject to driving and working time constraints. A new genetic algorithm with specialized crossover and mutation operators is developed and used to solve the problem, and results are compared with a math model and with state-of-the-art. The developed GA performed well in terms of solution quality and convergence speed. Center, Athens, OH, 45701, United States of America, sm774113@ohio.edu, Gursel Suer, Can Celikbilek Chair: Yi Liao, Southwestern University of Finance and Economics, Liutai Ave 555, School of Business Administration, Chengdu, China, yiliao@swufe.edu.cn 1 - Conflict Prevention and Detection for Autonomous and Connected Vehicles Xin Chen, Assistant Professor, Southern Illinois University, P.O. Box 1805, Edwardsville, IL, 62034, United States of America, xchen@siue.edu, Shimon Y. Nof An autonomous vehicle is capable of sensing its environment and navigating without human input. Conflicts between vehicles and between vehicles and transportation infrastructure are unavoidable. In this research, the authors develop a common language structure to represent domain knowledge in autonomous vehicles and apply algorithms and protocols to detect and prevent conflicts. 2 - Effective Vehicle Identification and Authentication Mechanism for Intelligent Transportation System Joonsang Baek, Khalifa University, Al Saada St. and Muroor Rd., Abu Dhabi, United Arab Emirates, joon.baek@kustar.ac.ae, Young-ji Byon Inspired by Internet of Things (IoT), it is possible to develop an identification mechanism for ITS, which is based on the unique vehicle identification number (VIN). Such identification mechanism would provide a certain level of privacy, which will assist traffic monitoring without compromising drivers’ identities by utilizing a strong authentication mechanism based on message authentication codes. WB71 71-Room 202B, CC Transportation Operations I Contributed Session

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