2015 Informs Annual Meeting

TB69

INFORMS Philadelphia – 2015

TB68 68-Room 201B, CC

4 - Can Time Buffers Lead to Delays? The Role of Operational Flexibility

Milind Sohoni, Associate Professor Of Operations Management And Sr. Associate Dean Of Programs, Indian School of Business, Gachibowli, Indian School of Business, Gachibowli, Hyderabad, Pl, 500032, India, milind_sohoni@isb.edu, Sanjiv Erat In operating systems where the feasible start time of activities is uncertain, the actual buffers for conducting the activities are distinct from scheduled buffers. We study how, and why, do these buffers affect operating performance? We propose a theoretical model and evaluate its empirical content and predictions using airline industry data. Our main result shows that both buffers impact performance and their effects are moderated by flexibility. Thus ex-ante plans must consider flexibility. TB67 67-Room 201A, CC Advances in Vehicle Routing Problem and its Variants Sponsor: TSL/Freight Transportation & Logistics Sponsored Session Chair: Ibrahim Capar, The University of Alabama, Box 870226, Tuscaloosa, AL, United States of America, icapar@cba.ua.edu 1 - The Vehicle Routing Problem with Drones: A Worst-case Analysis Xingyin Wang, University of Maryland, Mathematics department, University of Maryland, College Park, MD, 20742, United States of America, wangxy@umd.edu, Stefan Poikonen, Bruce Golden We introduce the Vehicle Routing Problem with Drones (VRPD). A fleet of trucks equipped with drones delivers packages to customers. Drones can be dispatched from and picked up by the trucks at the depot or the customer locations. The objective is to minimize the maximum duration of the routes. We compare VRPD to the min-max Vehicle Routing Problem from a worst-case perspective and show that the maximum savings from using the drones depends on the number and the speed of the drones. 2 - Online and Open Vehicle Routing Problem with Split Delivery Ibrahim Capar, The University of Alabama, Box 870226, Tuscaloosa, AL, United States of America, icapar@cba.ua.edu, Burcu Keskin We consider an online, open vehicle routing problem with split deliveries. This type of problem is usual for companies that use common carriers with TL, LTL, or container services. We develop an integer programming model and propose a reduction technique to solve real life problem with commercial software. We investigate the effect of lead time on cost and outstanding orders and explore different policies to minimize total cost. We show more than eight percent savings compared to the literature. 3 - Distributionally Robust Adaptive Vehicle Routing Arthur Flajolet, MIT, Operations Research Center, 77 Massachusetts Avenue, Bldg. E40-149, Cambridge, MA, 02139, United States of America, flajolet@mit.edu, Patrick Jaillet, Sebastien Blandin We consider an adaptive solution to the vehicle routing problem with stochastic travel times with the objective of minimizing a risk function of the lateness. To mitigate the impact of the lack of information on the travel times, we develop a distributionally robust dynamic programming formulation for risk-averse travelers and illustrate the practicality of the approach with field data from the Singapore road network. 4 - A Metaheuristic for the Electric Vehicle Routing Problem with Recharging Stations and Time Windows Site Wang, Graduate Student, Clemson University, 854 Issaqueena Trail, APT908, Central, SC, 29630, United States of America, sitew@clemson.edu, Eric Huang, Scott Mason In this study, we consider electric vehicles and recharging stations in the vehicle routing problem with time windows. We examine two objectives for this problem, separately and in concert, to provide insights for the location-routing problem with time windows. Due to the problem’s complexity, we demonstrate the efficacy of our two-phase metaheuristic that combines variable neighborhood search and Tabu search for practical-sized problems.

TSL Invited Cluster Keynote Address Sponsor: Transportation, Science and Logistics Sponsored Session Chair: Irina Dolinskaya, Northwestern University, 2145 Sheridan Road, Evanston, IL, 60208, United States of America, dolira@northwestern.edu 1 - Stochastic Vehicle Routing: An Overview and Some Research Directions Michel Gendreau, Full Professor, École Polytechnique de Montréal, P.O. Box 6128, Station Centre-ville, Montreal, QC, H3C 3J7, Canada, michel.gendreau@cirrelt.ca While Vehicle Routing Problems have now been studied extensively for more than 50 years, those in which some parameters are uncertain at the time where the routes are made have received significantly less attention, in spite of the fact that there are many real-life settings where key parameters are not known with certainty. In this talk, we will examine the main classes of Stochastic Vehicle Routing Problems: problems with stochastic demands, stochastic customers, and stochastic service or travel times. We will emphasize the main approaches for modeling and tackling uncertainty: a priori models, a posteriori approaches, and chance-constrained models. The end of the talk will devoted to a brief presentation of some interesting research directions in this area. TB69 69-Room 201C, CC Joint Session TSL/Public Sector: Health-care, Education, and Emergency Applications of Logistics Sponsor: Transportation, Science and Logistics Sponsored Session Chair: Sung Hoon Chung, Binghamton University, P.O. Box 6000, Binghamton, NY, United States of America, schung@binghamton.edu 1 - Public Transportation Planning for Mass-Scale Evacuations Rahul Swamy, Graduate Research Assistant, University at Buffalo (SUNY), 412 Bell Hall, Buffalo, NY, Jee Eun Kang, Rajan Batta This research provides a public transportation planning strategy in an urban setting for evacuating population groups to safe locations before a mass-scale disaster. Under the objective of maximizing the number of evacuees, the proposed model first identifies pickup locations and then constructs special type of routing to serve a time-varying demand. 2 - Minimizing the Cost of Routing Blood Collection Vehicles Okan Orsan Ozener, Ozyegin University, Cekmekoy, Istanbul, Turkey, orsan.ozener@ozyegin.edu.tr We study the routing of blood collection vehicles to minimize the total routing costs. Donated blood has to be processed within a certain amount of time. We analyze the routing decisions and propose an integrated framework to minimize the total cost while collecting a pre-specified number of donations. 3 - A Heuristic for School Bus Routing of Special-education Students Hernan Caceres, SUNY Buffalo, 342 Bell Hall, Buffalo, NY, United States of America, hernanan@buffalo.edu, Rajan Batta, Qing He The problem of routing special-education students differs in many aspects with that of routing regular students. A bus can be configured to also support wheelchairs, students may be served differently depending on their disability, and they need to be picked up and dropped off in their homes. In our study we modeled a mixed integer program that accounts for these and other characteristics. We use column generation to find approximated solutions for real and benchmark instances. 4 - Disaster Relief Routing under Uncertainty: A Robust Optimization Approach Sung Hoon Chung, Binghamton University, P.O. Box 6000, Binghamton, NY, United States of America, schung@binghamton.edu, Yinglei Li We explicitly consider uncertainty in travel times when planning vehicle routes for delivering critical supplies to the affected population in need in the aftermath of a large disaster. In particular, we propose the robust optimization approach to minimize the impact of uncertainty and eventually to achieve enhanced resilience in the aftermath of disasters. We also explore several numerical methods and algorithms.

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