2015 Informs Annual Meeting

WD71

INFORMS Philadelphia – 2015

WD71 71-Room 202B, CC Transportation Operations III Contributed Session Chair: Sara Saberi, PhD Candidate, University of Massachusetts Amherst, Department of Operations and Information, Isenberg School of Management, Amherst, MA, 01003, United States of America, ssaberi@som.umass.edu 1 - Vehicle Routing for Urban Drainage Operations: A VRP with Stochastic On-site Durations Hamid Zaman, Graduate Student, University of Alberta, 9105 116 Street NW, Edmonton, AB, Canada, hzaman@ualberta.ca, Mohamed Al-hussein, Ahmed Bouferguene Operational preventive maintenance of urban drainage network involves various short-duration flushing/cleaning activities performed at selected locations across the city, which results in large amount of travel. Moreover, the stochastic nature of the on-site activity durations can lead to unused time at the end of work shifts. This study thus formulates drainage operations scheduling as a combinatorial optimization problem which minimizes the aforementioned travel and unused times. 2 - Operational Flexibility in the Truckload Trucking Industry Hossein Zolfagharinia, Wilfrid Laurier University, 125 Lincoln Road, Waterloo, ON, N2J2N9, Canada, hzolfagharinia@wlu.ca, Michael Haughton Inspired by a real-life operating carrier, this study addresses a dynamic pickup and delivery problem with full truckload (DPDPFL) for local operators. The main purpose of this work is to investigate the impact of potential factors on the carriers’ operational efficiency. These factors, which are usually under the managerial influence, are diversion capability, re-optimization interval, and advance load information (ALI). 3 - An Integrated Multi-Ship Crane Allocation in a Transshipment Container Terminal Nabil Nehme, Assistant Professor, Lebanese American University, Byblos, Lebanon, nabil.nehme01@lau.edu.lb, Bacel Maddah, Isam Kaysi This research investigates the integration between the quay and yard sides for multiple berthing ships with transshipment containers. An integer linear programming model is formulated to minimize the total number of cranes used in both quay and yard sides for all berthing ships unloading at the same time horizon. The number of containers unloaded is determined for each crane used, quay location and for the storage location of containers on the yard per berthing ship. 4 - A Continuous Approximation Model for Logistic Distribution System Delivered by Trucks and Drones Li Yu Shan, PhD, Tsinghua University, Beijing Haidian Tsinghua University, Shuenn-Der Building, 615 South, Beijing, 100084, China, lyslys_1990@126.com This paper presents a continuous approximation model to evaluate cost of Logistics distribution model. The problem is a realistic variant of vehicle routing problem,in which expresses are delivered by trucks and drones. With Amazon’s Prime Air UAVs project,many companies pay attention to deliver goods with UAVs. Aim to evaluate economy of drones and build routing costs model with CA method. Analyze parameters of model and provide some insights for managers with ensuing decision-making reference. 5 - Supply Chain Network Competition in Price and Quality with Multiple Manufacturers and Carriers Sara Saberi, PhD Candidate, University of Massachusetts Amherst, Department of Operations and Information, Isenberg School of Management, Amherst, MA, 01003, United States of America, ssaberi@som.umass.edu, Anna Nagurney, Shivani Shukla, Jonas Floden We develop multitiered static and dynamic supply chain network models with manufacturers and freight service providers (carrier) with multiple modes of shipment competing on price and quality. They maximize their utilities while considering the consequences of the competitors’ prices and quality levels. An algorithm tracking the evolution of the strategic variables over time through discrete-time adjustment is presented. The framework is illustrated numerically and its practicality demonstrated.

WD72 72-Room 203A, CC Image and Functional Data Analysis: Methods and Applications Sponsor: Quality, Statistics and Reliability Sponsored Session

Chair: Kamran Paynabar, Georgia Institute of Technology, 755 Ferst Drive, Atlanta, GA, 30332, United States of America, kamran.paynabar@isye.gatech.edu 1 - Porosity Detection in Additive Manufacturing using Spatial Statistical Model Zhenyu Kong, Associate Professor, Virginia Tech University, 123 Durham Hall (MC 0118) 1145 Perry Str, Blacksburg, VA, 24061, United States of America, zkong@vt.edu, Jia (peter) Liu, Prahalad Rao In order to realize nondestructive quality monitoring for additive manufacturing (AM), we propose a nonparametric spatial statistical model to monitor porosity in AM products. We uses sliced images acquired by Micro CT to estimate the spatial distribution of porosity by employing Dirichlet process model, which can effectively the nonstationarity of the spatial distribution. 2 - Calibrating Functional Parameters in Computer Models, A Case Study Matthew Plumlee, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI, 48109, United States of America, mplumlee@umich.edu The output from a computational model depends on a set of parameters which are unknown, but a modeler can estimate them by collecting physical data. In the described study of the ion channels of ventricular myocytes, our parameter of interest is a function as opposed to a scalar or a set of scalars. New methods are devised to address this unique situation. 3 - A Degradation-based Prognostic Model using Image Data Xiaolei Fang, Georgia Tech, 1546 Woodlake Dr. NE, Apt. F, Atlanta, GA, 30329, United States of America, xfang33@gatech.edu, Kamran Paynabar, Nagi Gebraeel Due to the rapid development of sensing technology, it is possible to capture the degradation process of engineering systems using sequential image data. In this talk, we present a novel prognostic model utilizing degradation-based image data. Maintenance/Reliability Models Sponsor: Quality, Statistics and Reliability Sponsored Session Chair: Kai He, University of Pittsburgh, 1048 Benedum Hall, 3700 O’Hara Street, Pittsburgh, PA, 15261, United States of America, kah167@pitt.edu 1 - Competitive and Cooperative Game-theoretic Models for Usage-based Lease Contracts Maryam Hamidi, PhD Candidate, University of Arizona, 1127 E. James E. Rogers Way, Room 111, P.O. Box 210020, Tucson, AZ, 85721, United States of America, mhamidi@email.arizona.edu, Haitao Liao We develop competitive and cooperative game-theoretic models for lease contracts based on Nash equilibrium and total maximum profit, respectively. Under the contracts, the owner (lessor) rents an equipment which deteriorates with both age and usage to a user (lessee). The lessee determines the optimal lease period and usage rate, and the lessor develops a preventive maintenance policy. Our results illustrate that cooperation can significantly increase the profit, under certain conditions. 2 - On The Benefits of Condition-based Maintenance over Time-based Maintenance Bram De Jonge, University of Groningen, P.O. Box 800, 9700 AV, Groningen, Netherlands, b.de.jonge@rug.nl, Ruud Teunter, Tiedo Tinga Developments in condition monitoring technology have lead to an ongoing shift from time-based maintenance (TBM) to condition-based maintenance (CBM). Although CBM allows for more effectively planned maintenance, its performance strongly depends on the behavior of the deterioration process, severity of failures, required setup time, accuracy of the condition measurements, and amount of randomness in the failure level. This study points out how the relative benefit of CBM depends on these factors. WD73 73-Room 203B, CC

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