Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

WB32

4 - A Design of a Socially Inclusive Bikeshare System with Station Location Optimization Xiaodong Qian, University of California-Davis, Davis, CA, 95616, United States, Miguel A.Jaller Martelo Bikeshare programs are increasingly popular in the United States. However, far less attention has been paid to bikeshare programs’ potential to provide greater essential services for underserved communities. To date, there is virtually no quantitative research on how to design bikeshare systems for underserved communities. This research is aimed at designing a socially inclusive bikeshare system from the perspective of bikeshare station optimization. We will decide the optimized locations by solving a multi-objective optimization problem: 1) minimizing the differences of accessibility improvement between different communities and 2) maximizing the revenue generated. 5 - Estimating the Influence of Time Perception in Mode Choice for a Gondola Lift Transit System – Metrocable Medellin Daniela Jurado, Universidad Nacional De Colombia Sede Medellin, Carrera 78AA#56-49, Medell n, 050034, Colombia, Rodrigo Mesa Arango This research studies the effect of access-queue time on the choice between competing transit modes, i.e., bus and Metrocable (an unconventional gondola lift transit system), in Medellin, Colombia. Data from Metrocable’s critical influence areas are collected through stated/revealed preference surveys. Advanced econometric models are used to quantify the effect of queue waiting time perception on mode choice. Results support the implementation of policies to reduce queue-time subjectivities and increase system demand. 6 - A Fast Heuristic Algorithm for School Bus Routing Problems with Trip Compatibility Zhongxiang Wang, PhD Candidate, University of Maryland, Greenbelt, MD, 20770, United States, Ali Shafahi, Ali Haghani School bus planning problem is decomposed into the routing and scheduling subproblems. We present a new approach to incorporate the scheduling information (trip compatibility) into the routing such that the interrelationship between subproblems is considered in the decomposed problems. A novel heuristic is presented to solve the decomposed school bus routing problem with the trip compatibility. The first step finds an initial solution using an iterative minimum cost matching-based insertion heuristic. Then, the initial trips are improved using a Simulated Annealing and Tabu Search hybrid method. Experiments show our heuristic improves existing solutions up to 25% on the benchmark problems. n WB32 North Bldg 222B Practice- Vehicle Routing II Contributed Session Chair: Darweesh E. Salamah, Mississippi State University, MS, 39763- 9542, United States 1 - The Model and Optimization of Container Drayage Problem in Truck Platooning Mode Jintao You, PhD Candidate, Graduate School at Shenzhen, Tsinghua University, E302F, Datong building, University Town, Shenzhen, 518055, China, Zhaojie Xue This paper investigates a container drayage problem in which trucks operate in platoon mode. One fleet can be operated by only one driver in the leading truck, while the rest trucks follow the leading one by using semi-autonomous driving technique. A group of leading manned trucks and following unmanned trucks are synchronously scheduled to serve a set of full-container-load customers within a time horizon. A general mathematical model is proposed to describe this problem as a variant of VRP with alterable capacity, temporal constraints and OD pairs. Considering the NP essence of this problem, a local search based heuristic method is proposed to solve the problem. 2 - An Optimized Route for Q100’s Bert and Kristin to Visit All Jersey Mike’s Subs in Atlanta for Charity Jessica Rudd, PhD Student, Kennesaw State University, 1000 Chastain Rd, Kennesaw, GA, 30144, United States, Lauren Staples, Sanjoosh Akkineni, Andrew Henshaw The project built an optimal route for two popular radio show hosts to visit each of the 37 Atlanta area Jersey Mikes Subs in one day. This supported a fundraising effort to send children with chronic and terminal illnesses to Disney World. We developed a combined approach to the Multiple Traveling Salesman Problem that pairs a custom genetic algorithm with Google’s combinatorial optimization solver. 3 - Work Crew Routing Problem for Infrastructure Network Restoration Nazanin Morshedlou, University of Oklahoma, Norman, OK, 73071, United States, Kash Barker, Andres David Gonzalez This presentation introduces a synchronized routing problem for planning and scheduling restorative efforts for infrastructure networks in the aftermath of a

disruptive event. In this problem, a set of restoration crews are dispatched from depots to a road network to restore the disrupted infrastructure network. Two mathematical formulations are presented to scheduling and sequencing disrupted network components to restoration crews and route the crews towards disrupted components to maximize network resilience progress in any given time horizon. We further introduce a feasibility algorithm to derive a strong initial solution for the routing restorative capacity problem. 4 - Management of Charging Stations’ Interrelated Electrical Infrastructure Systems under Major Disruption: A Mathematical Model Darweesh E. Salamah, Mississippi State University, Mississippi State, MS, 39762, United States, Mohannad Kabli, Mohammad Marufuzzaman, Salem Batiyah Electric vehicles are envisioned to become the main transportation mode for the future. Electrical Infrastructure is a vital component in the operation of electric vehicles’ charging stations. Building a resilient electric system that minimizes the power restoration time is essential for a smooth operation of future transportation modes. This paper aims to fortify the connections within and in between all related electrical structures and charging stations to face against any deliberate or sudden power disruptions. A mathematical model is built with the aim of minimizing disruption costs. Vehicle Routing Contributed Session Chair: Jihyun Jo, Pennsylvania State University, 234 Leonhard Building, University Park, PA, 16802, United States 1 - Routing Optimization in Bulk Transportation with Compatibility Constraints Ugandhar Delli, Graduate Research Assistant, Kansas State University, Manhattan, KS, 66502, United States, Ashesh Kumar Sinha We analyze bulk transportation with specialized wash operation after every delivery. Unlike traditional vehicle routing problems, the interaction properties of chemical/liquid bulk orders must also be accounted for that impose complex product-sequencing constraints. We propose an integrated approach that combines the efficacy of column generation and efficient graph decomposition to account for compatibility constraints while optimizing trailer-wash-order combinations. 2 - A Risk Based Border Surveillance Using Drones with a Dynamic Wireless Charging System Navid Ahmadian, University of Houston, Houston, TX, United States, Gino J. Lim, Seon Jin Kim, Maryam Torabbeigi We propose a risk-based surveillance model using unmanned aerial vehicles (UAVs) for border patrol. The short flight duration of drones is a major drawback for such a system. So, we use the dynamic wireless charging system to increase the flight time of the drones in real time. Assuming that each location is associated with a different priority of coverage, a risk-based MIP model is proposed to increase the frequency of visiting the highly critical locations. To accomplish our goal, we first split the total area into sub-areas based on the risk associated with their location, and assign a drone to each sub-area. Then, we find the optimal path and also location of the E-line system related to each drone. 3 - Asymmetric Formulations for the Symmetric Capacitated Vehicle Routing Problem Sune Lauth Gadegaard, Assistant Professor, Aarhus University, Fuglesangs Alle 4, Aarhus V, 8210, Denmark, Jens Lysgaard In this talk, we present results obtained using new polynomial formulations for the symmetric capacitated vehicle routing problem. The formulations decompose each route into two paths originating at the depot and meeting at the customer having the largest index (the peak customer) on the route. We outline a branch and bound like algorithm exploiting the formulation and present computational results. 4 - Multi Objective Models for Dynamic Vehicle Routing Problem in City Logistics Gitae Kim, Hanbat National University, Dept. of Industrial Management Engineering, School of Engineering, Daejeon, 34158, Korea, Republic of Stakeholders such as shippers, carriers, residents, and local authorities in city logistics have their own different objectives that may cause conflicts each other. Accordingly, the city vehicle routing problem could consider the benefits of stakeholders. However, there are lack of studies considering the concerns of multiple stakeholders. This paper investigates the multi objective models for the vehicle routing problems in city. We consider both dynamic and stochastic conditions for the vehicle routing problem. The stochastic dynamic programming model combined with multi objective model is proposed. We also provide the numerical results to present the models. n WB33 North Bldg 222C

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