2016 INFORMS Annual Meeting Program

TC61

INFORMS Nashville – 2016

2 - Reliability Of Transit Connections For Informed Traveler Decision-making Michael Redmond, University of Iowa, Iowa City, IA, 52240, United States, michael-a-redmond@uiowa.edu, Ann Melissa Campbell, Jan Fabian Ehmke When faced with the decision of journeying from an origin to a destination, travelers have a multitude of options and criteria for making this decision. Travel websites generally look at price and travel time, leaving out the important component of reliability. We compute the probability of making all of the required connections and arriving on-time at the destination and refer to this as reliability. We utilize publicly available airline data to model the probability distributions and will present the reliability associated with different paths between several origin and destination pairs involving different hubs and start times. 3 - Stochastic Multi-period Orienteering With Time Windows And Uncertain Customer Adoption Shu Zhang, Chongqing University, Chongqing, China, zhangshu@cqu.edu.cn, Jeffrey W Ohlmann, Barrett Thomas We introduce an orienteering problem in which a sales representative visits customers over a multi-period horizon to increase the chance of customer adoption. Each customer’s adoption likelihood is uncertain and evolves stochastically over the horizon. The salesperson may experience queueing after arrival and the wait times are uncertain. We model the problem as a Markov decision process and propose heuristic approaches to facilitate decision making. In the computational experiments, we demonstrate the effectiveness of our heuristic methods on various customer behaviors. 4 - Application Of A Robust Approach For Vessel Crew Scheduling Seda Sucu, University of Strathclyde, 130 Rottenrow Gardens, Sir Willam Duncan Building, Glasgow, G4 0QE, United Kingdom, seda.sucu@strath.ac.uk, Kerem Akartunali, Robert van der Meer Crew scheduling problems have a significant place among the NP-Hard problems, and are very popular especially in the transportation settings. Although there are many studies in airline crew scheduling, there is a lack of literature for crew scheduling for offshore supply vessels. In our problem, we focus on having a robust crew schedule to handle unexpected weather conditions and changes in crew members’ conditions for a global vessel company with long planning horizon. Sustainability and Resilience Sponsored: TSL, Urban Transportation Sponsored Session Chair: Mohammadali Shirazi, TAMU, College Station, TX, United States, alishirazi@email.tamu.edu 1 - A Fast Method To Estimate The Minimal Revenue Tolls In Large-scale Roadway Networks Mohammadali Shirazi, TAMU, alishirazi@email.tamu.edu The minimum toll revenue problem is one of the models that were proposed for toll pricing. When applied to real and large-scale road networks, this model is difficult to be solved optimally in reasonable time, due to its large size. We propose a fast method to estimate the minimal revenue tolls in large-scale road networks using the dynamic penalty function method. The proposed method also allows measuring the improvement of the network when the system flows are considered only for a subset of network links. 2 - Pothole Repair Planning Fatemeh Aarabi, University at Buffalo, faarabi@buffalo.edu Potholes degrade the functionality of roadway networks (throughput of traffic flow) in addition to concerns of safety and vehicle damages. A suitable repair planning strategy is developed to minimize total traffic flow throughput degraded over time. The proposed model determines the optimal decisions of repair segment, type, and timing given limited resources. We apply the proposed model to a New York City case study. 3 - Joint Optimization Of Traffic Rationing Schemes And Transit Services Under Environmental And Mobility Considerations Daniel Rodriguez Roman, URPM, daniel.rodriguez6@upr.edu An optimization-based approach for the design of traffic rationing schemes is proposed that accounts for: (1) the environmental goals of urban planners, (2) the budgetary and fleet size limitations of transit agencies, and (3) the mobility preferences of travelers. The proposed optimization problem can be used to determine traffic rationing levels and related transit service adjustments that minimize the health impacts of air pollution and the traveler dissatisfaction caused by rationing programs, subject to pollutant concentration and transit budget constraints. A surrogate-assisted, multi-objective differential evolution algorithm is presented for the proposed problem. TC60 Cumberland 2- Omni Network Optimization for Efficiency,

4 - Modeling And Enhancing The Resilience Of Complementary Transportation Systems Saumya Sangoi, Purdue University, West Lafayette, IN, 47906, United States, ssangoi@purdue.edu, Xiaozheng He, Srinivas Peeta This study proposes a new resilience measure by capturing the complementarity among interdependent transportation systems, such as bus and metro systems. Based on the proposed resilience measure, we construct an optimization model to identify the optimal allocation of resources and maximize the interdependent system resilience under a budget constraint. Numerical examples are constructed to evaluate the effectiveness of the optimization model on a network comprising bus and metro systems. TC61 Cumberland 3- Omni Stochastic Network Design Sponsored: TSL, Freight Transportation & Logistics Sponsored Session Chair: Mike Hewitt, Loyola University Chicago, NA, Chicago, IL, NA, United States, mhewitt3@luc.edu 1 - Scheduled Service Network Design With Stochastic Travel Times Teodor Gabriel Crainic, Professor, Universite du Quebec a Montreal, Case postale 8888, succursale Centre-ville, Montreal, QC, H3C 3P8, Canada, TeodorGabriel.Crainic@cirrelt.net, Giacomo Lanza, Nicoletta Ricciardi, Walter Rei We propose to study a SSND problem focusing on the uncertainty related to the variability in travel times and the respect of service quality targets, while aiming for a cost-effective operation plan. We will discuss the issues and modeling challenges, and present a two-stage stochastic programming formulation with wimple recourse. The results of a proof-of-concept analysis will also be presented. 2 - Multi-commodity Stochastic Network Design Stein W Wallace, Norwegian School of Economics, stein.wallace@nhh.no, Stein W Wallace, University of Sichuan, Chengdu, China, stein.wallace@nhh.no, Congshi Sun We investigate the quality of the solution to the expected value problem by checking the Value of the Stochastic Solution VSS, the quality of the skeleton (that is, taking the discrete variables from the expected value problem and letting a stochastic linear program set the capacities) and finally by checking if the expected value problem can be upgraded to a good solution for the stochastic case. Numerical results are reported. For most situations the skeleton is very good, so for these problems, it seems enough to solve a deterministic MIP and a stochastic LP, rather than a stochastic MIP. 3 - Dynamic Load Planning For Less-than-truckload Carriers Luke Marshall, Georgia Institute of Technology, Atlanta, GA, In practice, deterministic service network design for LTL problems on a given time horizon, can yield poor results if the quantities for future commodities have been estimated from data with high fluctuations. We investigate a sampled scenario based modelling approach that aims to improve solution quality on real-life, large scale instances, while constraining computational time. 4 - Stochastic Interdependent Network Design Problem Andrés D González, Rice University, 6100 Main St., MS-318, Houston, TX, 77005, United States, andres.gonzalez@rice.edu Diverse models now exist to study the resilience of interdependent networks. Nevertheless, the prevailing methods are post-event schemes designed to identifying recovery strategies for particular disaster instances, making it difficult to extend these for pre-event decision making. In this work, we present a new methodology that considers the uncertainty associated with the occurrence of a destructive event, fusing both pre- and post-event decision analysis into a two- stage optimization problem, effectively enabling the stochastic resilience optimization of interdependent networks. Leonardo Dueñas-Osorio, Andres L Medaglia, Mauricio Sánchez-Silva, Andrew J Schaefer United States, luke.jonathon.marshall@gmail.com, Martin W P Savelsbergh, Natashia Boland, Alan Erera, Iman Dayarian

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