2015 Informs Annual Meeting

WE71

INFORMS Philadelphia – 2015

4 - Decomposition Method for Revenue Management Problem of Multi-period Multi-class High Speed Rail Hasan Manzour, Industrial & Systems Engineering, University of Washington, Box 352650, Seattle, WA, 98195-2650, United States of America, hmanzour@uw.edu, Zhe Liang, Ying Qin, W. Art Chaovalitwongse We study a multi-period multi-class rail passenger revenue management (MPMC- RPRM) problem in which the unsatisfied demand from a previous period can be recaptured by the later periods. The original MIP model is hard to solve. Therefore, we present a Benders decomposition solution approach incorporating some heuristics. In addition, Benders cuts are strengthened to facilitate faster convergence and improved computational efficiency. We perform the analysis on a real case study. WE69 69-Room 201C, CC Intelligent Traffic Signal Control Sponsor: TSL/Intelligent Transportation Systems (ITS) Sponsored Session Chair: K. Larry Head, University of Arizona, Tucson, AZ, United States of America, larry@sie.arizona.edu 1 - Smart Signal Systems for Urban Road Networks Stephen F. Smith, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, United States of America, sfs@cs.cmu.edu, Gregory J. Barlow, Zachary B. Rubinstein, Isaac Isukapati, Xiao-Feng Xie Traffic optimization in urban environments presents special challenges, due to issues of scale, uncertainty, and competing, time-varying dominant flows. We formulate and analyze a decentralized approach to signal control in this setting, where each intersection optimizes locally sensed traffic in real-time and exchanges plans with neighbors to achieve coordinated behavior. 2 - Intelligent Traffic Control in a Connected Vehicle Environment An intelligent traffic control framework in a connected vehicle environment is proposed. A phase allocation algorithm optimizes the signal timing based on different objectives considering both mobility (delay) and safety (dilemma zone protection). Additional constraints from signal priority are integrated into the same framework. 3 - Unified Section Level Priority and Intelligent Traffic Signal Control Byunho Beak, University of Arizona, Tucson, AZ, United States of An integrated priority control and adaptive signal control model is developed that can intelligently consider connected vehicles and priority eligible vehicles at both intersection level and section level. The model coordinates optimal priority strategies between two or more consecutive intersections and also guarantees connected vehicles progression within the intersections. 4 - Solving Simultaneous Route Guidance and Traffic Signal Optimization Problem using Space-time-phase Hypernetwork Pengfei Li, Xuesong Zhou, Pitu Mirchandani This talk addresses the simultaneous route guidance and traffic signal optimization problem. A space-time-phase hypernetwork is used to explicitly represent the traffic signal control mechanism and time-dependent paths. We develop a Lagrangian-relaxation-based problem decomposition framework, and the subproblems are solved using finite-horizon dynamic programming algorithms. WE70 70-Room 202A, CC Vehicle Routing IV Contributed Session Chair: Ozgun C. Demirag, Penn State Erie, Black School of Business, Erie, PA, United States of America, ozc1@psu.edu 1 - A Fast Algorithm for Solving the Static Rebalancing Problem in Bike Sharing Systems Aritra Pal, Doctoral Student, University of South Florida, Tampa, Tampa, FL, 33612, United States of America, aritra1@mail.usf.edu, Yu Zhang We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm for solving the Static Rebalancing Problem in Yiheng Feng, University of Arizona, Tucson, AZ, yihengfeng@email.arizona.edu, Mehdi Zamanipour, Shayan Khoshmagham, K. Larry Head America, beak@email.arizona.edu, Mehdi Zamanipour, K. Larry Head, Yiheng Feng, Shayan Khoshmagham

Bike Sharing Systems. Computational experiments on a set of benchmark instances previously used in the literature, demonstrate that the presented algorithm is both more effective and more efficient than a tabu search algorithm and highly competitive with exact algorithms previously reported in the literature. 2 - Trip Generation Models for Medellin Metropolitan Area Ivan Sarmiento, Associate Professor, Universidad Nacional de Colombia at Medellin, Calle 65 No.78 - 28, M1-201, Medellin, A freight survey with a sample of 2,984 commercial establishments in Medellin, Colombia was conducted in 2012 to characterize the cargo movements and patterns in the city. Based on the survey, a series of trip generation models are estimated. A complete analysis of the variables and their influence on trip generation are considered along with the characteristics of the freight movements in the area 3 - Continuum Approximation Modeling of Freight Distribution Systems Mahour Rahimi, Assistant Professor, University of Massachusetts, Amherst, Department of Civil & Environmental Eng., 130 Natural Resources Road, Amherst, MA, 01003, United States of America, gonzales@umass.edu, Eric Gonzales This study presents a continuous approximation model for truck deliveries which relate the operating parameters to the characteristics of the service and network, service area, and demand rate. The objective of this study is to minimize the total cost of distributing multicommodity freight from an origin to randomly distributed points, with or without transshipments, and within a limited amount of time. Two different distribution methods are considered: peddling, and peddling with transshipment. 4 - Tabu Search Heuristic for the Heterogeneous Vehicle Routing Problem on a Multigraph Ozgun C. Demirag, Penn State Erie, Black School of Business, Erie, PA, United States of America, ozc1@psu.edu, Janny Leung, David S.w. Lai We study a time-constrained heterogeneous vehicle routing problem on a multigraph. We formulate the problem as a mixed-integer linear programming model and develop a tabu search heuristic that efficiently addresses computational challenges due to parallel arcs. Numerical experiments show that the heuristic is highly effective. WE71 71-Room 202B, CC Transportation- Public Contributed Session Chair: Subasish Das, Research Associate, University of Louisiana at In Delhi the buses often arrive at bus-stops in clusters that causes long waiting time as well as more variations in headways. Due to clustering of buses, the average waiting time for public bus users in Delhi is often more than 30 minutes. Due to this high and uncertain waiting time, bus commuters are face issues with punctuality. This work addresses the problem of lack of punctuality associated with the existing bus system by reduced bus bunching in the mixed traffic conditions of Delhi. The approach, if used, can provide significant benefits in the mean as well as variability of travel time. 2 - Dynamic Transit Service Network Design under Capacitated User Equilibrium Conditions Jiangtao Liu, Arizona State University, Ira A. Fulton Schools of Engineering, Tempe, AZ, United States of America, jliu215@asu.edu, Xuesong Zhou This talk will discuss how to address emerging modeling issues in transit service network design such as time-dependent capacitated user equilibrium, system- wide impact of dynamic service line scheduling under equilibrium conditions. We will develop a single level model with a Lagrangian relaxation based approximation method to rapidly find close-to-optimal solution subject to budgetary, UE and capacity constraints. Colombia, irsarmie@unal.edu.co, Ivan Sanchez-Diaz, Jose Holguin-Veras, Carlos A. Gonzalez-Calderon Lafayette, P.O. Box- 44886, Lafayette, LA, 70504, United States of America, subasishsn@gmail.com 1 - Bus Bunching Modeling for Mixed Traffic in Delhi Hemant Suman, Research Scholar, IIT Delhi, Hauz Khas, New Delhi, 110016, India, hemantsmn@gmail.com, Nomesh Bolia

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