2016 INFORMS Annual Meeting Program

TC72

INFORMS Nashville – 2016

TC70 Acoustic- Omni Transportation, Planning II Contributed Session

TC71 Electric- Omni Vehicle Routing IV Contributed Session Chair: Jimena A. Pascual, P. Universidad Católica de Valparaíso, Valparaíso, Chile, jimena.pascual@pucv.cl 1 - Using Drones To Minimize Waiting Times Of Customers Mohammad Moshref-Javadi, PhD Candidate, Purdue University, School of Industrial Engineering, 315 N. Grant St., West Lafayette, IN, 47907, United States, moshref@purdue.edu, Seokcheon Lee Drone is an emerging technology which can be used in logistics operations for more efficient transportation. We propose a new problem which incorporates drones in delivery processes to minimize waiting time of recipients. 2 - A Mathematical Programming Framework That Integrates Customer Decisions Within The Distribution Planning Of Petroleum Products This work develops a methodological framework for designing the daily distribution and replenishment operations of petroleum products by simultaneously considering the perspectives of both the transporter and its customers. We provide empirical evidence that minor alterations to the customer requirements, triggered by some strategic decisions by the transporter, can in turn fexibilize the transporters’ restrictions, allowing for better routing strategies that reduce late deliveries. Therefore, The main objective of this work is studying the interactions that exist between these strategic and operational decisions within a unied approach. 4 - Solving Multi Period Multi Traveling Salesmen Problem With Time Windows: Comparison Of Heuristic Approaches Haluk Yapicioglu, Assist. Prof. Dr., Anadolu University, Anadolu Universitesi Yunusemre Kampusu, Proje Birimi Ogrenci Merkezi Kat: 1, Eskisehir, 26470, Turkey, hyapicio@anadolu.edu.tr The problem addressed in this study aims at minimizing number of university representatives visiting exam locations by departing from a central location and returning back. Visits to the exam locations must be done in specified time windows. The problem is modeled as a multi-period traveling salesmen problem with time window. Two stochastic optimization approaches based on simulated annealing and robust taboo search are used. For this a new solution representation is proposed. Finally, a method for obtaining travel distance and travel time matrices from Google Distance Matrix API is developed. The results obtained from a real case are discussed and future research directions are provided. 5 - Optimal Routing Of Unmanned Aerial Vehicles In Wind Fields Jimena A. Pascual, P. Universidad Católica de Valparaíso, Valparaíso, Chile, jimena.pascual@pucv.cl, Ricardo A. Gatica, Andrea Leticia Arias, Andrea Leticia Arias, Kundu Abhishake, Darío Canut De Bon, Timothy I Matis The power consumption of an Unmanned Aerial Vehicle (UAV) to overcome directional wind forces may be represented as a non-linear convex function of airspeed. As a result, the optimal flight path between two targets may not be Euclidean, and may have implications on the optimal sequencing of multiple targets. In this presentation, we present research related solving shortest path and traveling salesman type problems to determine the optimal flight path for UAVs, and discuss how this might be extended to other classes of unmanned vehicles, often referred to as UXVs. Yan Cheng Hsu, University at Buffalo, SUNY, 412 Bell Hall, Buffalo, NY, 14260, United States, yhsu8@buffalo.edu, Jose Luis Walteros, Rajan Batta

Chair: Bruce C Hartman, Professor, University of St Francis, 684 Benicia Drive #50, Santa Rosa, CA, 95409, United States, bruce@ahartman.net 1 - Modeling Wet Pavement Crashes

Michael Anderson, Professor, UAH, Civil Engineering, Huntsville, AL, 35899, United States, andersmd@uah.edu, Mehrnaz Doustmohammadi

Crashes when the pavement is wet are a significant issue within Alabama. This work develops models to identify the key roadway and pavement characteristics that are associated with wet pavement crashes. Additionally, the analysis will include the type of crash generally occurring and the cause of the crash associated with wet pavement. 2 - A Framework For Intelligent Decision Support System For Traffic Congestion Management System Mohamad kamal El Din Ahmad Hasan, Professor of Operations and Supply Chain Manag, Dept. of Quantitative Methods and Information Systems, CBA, Kuwait University, Department of Quantitative Methods and Information Systems, College of Business Administration, Kuwait University, P.O. Box 5486, Safat 13055, Kuwait City, 13055, Kuwait, mkamal@cba.edu.kw Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economic and development aspects of urban areas. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS- based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers. 3 - Locating Emergency Vehicles With An Approximate Queueing Model And A Meta-heuristic Solution Approach M. Altan Akdogan, Research Assistant, Middle East Technical University, Ankara, Turkey, aaltan@metu.edu.tr, Z Pelin Bayindir, Cem Iyigun In this study, optimal location decision of Emergency Service(ES) vehicles such as ambulances as a server-to-customer service is discussed. Spatial Queueing Model (SQM) is introduced for spatial networks in locating emergency vehicles in the literature. This study proposes a generalization of SQM for complete networks. Service times for the calls are differentiated for every demand call regarding the location of the responding vehicle and the demand call. The number of servers located in a single location is taken unrestricted. The effect of allowing multiple servers in a location is reported. A genetic algorithm is proposed to solve the model for which no closed-form expression exists. 4 - Toll Road Profit Maximization Under Mixed Travel Behaviors Of Cars And Trucks Xiaolei Guo, Associate Professor, University of Windsor, Odette School of Business, 401 Sunset Avnue, Windsor, ON, N9B 3P4, Canada, guoxl@uwindsor.ca, Da Xu, Guoqing Zhang This paper examines the profit maximizing behavior of a private firm which operates a toll road competing against a free alternative in presence of cars and trucks. Trucks differ from cars in value of time, congestion externality, pavement damage, and link travel time function. We assume that trucks choose routes deterministically (i.e., choose the route with the lowest actual cost) while cars follow stochastic user equilibrium in route choice (i.e., choose the route with the lowest perceived cost). 5 - Transportation, Jobs And Social Networks Bruce C Hartman, Professor, University of St Francis, 684 Benicia Drive #50, Santa Rosa, CA, 95409, United States, bruce@ahartman.net Bruce C Hartman, Professor, California State University Maritime, 200 Maritime Academy Drive, Vallejo, CA, 94590, United States, bruce@ahartman.net Logistics clusters provide economic benefit, but expansion has not produced proportionate sector job growth. We hypothesize a network effect not accounted for in traditional analysis. We apply egonets from social network analysis to a weighted network modeled by Total Requirements matrix data for 15 US industry clusters. We propose network measures of value creation and leverage for each sector. A quadrant assessment of our two measures classifies influence of industry sectors. Transportation and Wholesaling sectors create high leverage in the industries they touch, using relatively low value added.

TC72 Bass- Omni Supply Chain Mgt XI Contributed Session

Chair: Fang Fang, California State University, LA, 1250 S Alhambra Circle, Apt 18, LA, CA, 33146, United States, f.fang@umiami.edu 1 - Traceability And Supply Chain Design John F Kros, Vincent K. McMahon Distinguished Professor, East Carolina University, College of Business Dept of M&SCM, 3205 Harold Bate Building, Greenville, NC, 27858-4353, United States, krosj@ecu.edu, James Zemanek, Jon Kirchoff In light of recent issues, supply chain managers’ focus on product and service traceability has increased. While research on how/where disruptions occur and supply chain risk mitigation have taken center stage, the topic of traceability across the supply chain has received little attention. This research seeks to investigate the topic of traceability across the supply chain and what policies/procedures supply chain managers have implemented to trace their products/services within and across the supply chain.

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