2015 Informs Annual Meeting

SD69

INFORMS Philadelphia – 2015

SD66 66-Room 113C, CC Aviation Applications Section: Award Finalists Sponsor: Aviation Applications Sponsored Session Chair: Senay Solak, University of Massachusetts Amherst, Isenberg School of Management, Amherst, MA, 01003, United States of America, solak@isenberg.umass.edu 1 - Robust Aircraft Routing Chiwei Yan, Massachusetts Institute of Technology, 77 Massachusetts Avenue, E40-130, Cambridge, MA. United States of America, chiwei@mit.edu We propose a robust optimization approach to minimize total propagated delay in the aircraft routing problem, a setting first developed by Lan et al. (2006) and then extended by Dunbar et al. (2012). The major contribution of our model is that it allows us to model correlated flight leg delays that existing approaches cannot efficiently incorporate. Using both historical delay data and simulated data, we show our model outperforms the state-of-the-research stochastic approach. 2 - Optimization and Analytics for Air Traffic Management Michael Bloem, NASA, Ames Research Center, Moffett Field, CA, United States of America, michael.bloem@nasa.gov We discuss three types of decisions in the air traffic management system: (1) how to configure available airspace and other resources to ensure safe and efficient operations in a region of airspace, (2) how to assign a set of flights to a set of slots in an Airspace Flow Program, and (3) when to implement a Ground Delay Program. Chair: Mahir Yildirim, Turkey, mahiryldrm@sabanciuniv.edu 1 - Service Design for Liner Shipping with Service Levels Jan Fabian Ehmke, Assistant Professor, Freie Universität Berlin, Garystr. 21, Berlin, 14195, Germany, JanFabian.Ehmke@fu-berlin.de, Ann Campbell, Kevin Tierney We consider the liner shipping route design problem, where each port has a time window, and travel times between ports are assumed to be stochastic. We ensure that each time window is satisfied with a given service level while minimizing the costs of a single route. We investigate how different service levels affect the costs of a route. We also allow the model to increase the speed of a vessel to ensure the service level, and we analyze the trade-off between vessel costs and costs of speeding. 2 - Decision Support for Flexible Liner Shipping Johan Oppen, Norway, Johan.Oppen@hiMolde.no We present a transportation problem representing a combination of liner and tramp shipping, where using other modes of transportation is also an option. As an example, we consider transportation of palletized frozen fish from Russia and Norway to terminals in Norway, the Netherlands and the UK. We present a mathematical model for the planning problem associated with each tour and show that problem instances of realistic size can be solved to optimality using standard software. 3 - A Biased Random-Key Genetic Algorithm for the Container Pre-Marshalling Problem Kevin Tierney, Assistant Professor, University of Paderborn, Warburger Strafle 100, Paderborn, 33098, Germany, kevin.tierney@upb.de, Andre Hottung Container terminals re-order containers they are storing through a pre- marshalling process in order to streamline their operations. Even small pre-marshalling problems are difficult for state-of-the-art techniques to solve. We introduce a biased random-key genetic algorithm with several novel heuristics for solving the container pre-marshalling problem. Our approach can be easily integrated into a decision support system for terminal operators to help them increase port efficiency. SD67 67-Room 201A, CC Container-based Logistics Sponsor: TSL/Freight Transportation & Logistics Sponsored Session

4 - Scheduled Service Network Design Problems with Balance and Synchronization Constraints Mahir Yildirim, Turkey, mahiryldrm@sabanciuniv.edu, Tom Van Woensel, Theo Crainic In this study, we address the problem of scheduled service network design (SND) for container freight distribution along rivers, canals, and coastlines. We propose a new concise continuous-time mixed-integer linear programming model where the objective is to build a minimum cost SND and container distribution plan defining services, their departure and arrival times, as well as vehicle and container routing. The model is solved with an ALNS-based heuristic with specific neighborhood structures. SD68 68-Room 201B, CC Electric Vehicles I Sponsor: Transportation, Science and Logistics Sponsored Session Chair: Hong Zheng, Purdue University, United States of America, zheng255@purdue.edu 1 - Charging Efficiency Analysis of the Dynamic Charging Electric Vehicle Young Jae Jang, Assistant Professor, KAIST, 291 Daehak ro, Industrial and Systems Eng, KAIST, Daejeon, 305701, Korea, Republic of, yjang@kaist.ac.kr The Dynamic Wireless Charging Electric Vehicle (DWC-EV) charges the battery in the vehicle from a power transmitter embedded in the road. The advantage of the system is that the charge can be done while the vehicle is in motion. The KAIST On-Line Electric Vehicle (OLEV) is a commercially available DWC-EVs. We present the charging efficiency analysis of DWC-EVs with data collected from the OLEV. We discuss how the power transmitters are effectively allocated with the finding from the analysis. 2 - Adaptive Routing and Recharging Policies for Electric Vehicles Irina Dolinskaya, Northwestern University, 2145 Sheridan Road, Evanston, IL, 60208, United States of America, dolira@northwestern.edu, Timothy M. Sweda, Diego Klabjan Recharging costs for an electric vehicle (EV), which increase as the battery’s charge level increases, are fundamentally different than for conventional vehicles. Furthermore, the availability of charging stations along the way must be considered. We study the problem of finding an optimal routing and recharging policy for an EV in a grid network. We develop and analyze a variety of models depending on the amount and timing of information available to the EV driver while traveling. 3 - Electric Vehicle Routing and Network Design of Charging Station Locations An electric vehicle (EV) cannot travel beyond its range without stopping to recharge its battery. This study addresses two problems for EVs. We show that the EV routing subject to range feasibility and maximum number of stops can be reduced to a dynamic program solving the shortest path problem on an auxiliary network. We then present a mixed-integer linear programming formulation and a solution algorithm for the network design problem of determining the charging station locations. SD69 69-Room 201C, CC Facility Logistics II Sponsor: TSL/Facility Logistics Sponsored Session Chair: Clara Novoa, Associate Professor, Texas State University, 601 University Dr., San Marcos, TX, 78666, United States of America, cn17@txstate.edu 1 - New Aisle Designs for Order Picking Warehouses Sabahattin Ozden, Auburn University, Shelby Center, Auburn, United States of America, sgo0002@auburn.edu, Alice Smith, Kevin R. Gue We reveal results of a three year effort to find new aisle designs for order picking warehouses. We describe a computational system that searches all possible designs within a design class using an evolutionary strategy. To assess the fitness of a design, the system allocates SKUs to locations and then builds optimal routes from real orders. The results, we believe, are surprising and significant. Hong Zheng, Purdue University, United States of America, zheng255@purdue.edu, Xiaozheng He, Srinivas Peeta

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