ABSTRACT
A two-stage stochastic model is developed for intermodal facility location and freight distribution under random disruptions at shipper facilities and/or intermodal terminals (IMTs). The magnitude of the disruption and the impacted locations are uncertain parameters. A two-stage stochastic programming model is used to address supply uncertainty at shippers and throughput capacity uncertainty at IMTs. A level-method based decomposition approach and the L-shaped method are used to solve the model. The state of South Carolina in the U.S.A. is used as a case study with the goal of determining the set of IMT locations that minimise the total long-run network costs due to hurricane disruptions. A methodology is developed to generate realistic scenarios. The Freight Analysis Framework Version 4.5 data set is used to generate demands and supply, and k-means clustering is used with the Hurricane database (HURDAT2) to generate hurricane disruption scenarios. Sensitivity analyses are performed by varying the disruption probabilities, disruption duration, and direct shipping cost parameters. The results indicate that as disruptions increase, less disrupted intermodal facilities are opened. Also, as direct shipping costs increase, the long-term savings increase non-linearly for all magnitudes of disruptions.
Acknowledgments
This study was supported by the Center for Connected Multimodal Mobility (C2M2), a U.S. Department of Transportation Tier-1 University Transportation Center. Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of C2M2. The U.S. Government assumes no liability for the contents or use thereof.
Disclosure statement
No potential conflict of interest was reported by the author(s).
8. Data availability statement
Two data sources were used in this research and both are publicly available: (1) Freight Analysis Framework Version 4.5 (https://www.bts.gov/faf/faf4) and (2)Hurricane database HURDAT2 (https://www.nhc.noaa.gov/data/).
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Notes on contributors
Vishal Badyal
Vishal Badyal received his PhD and Master's degree in Industrial Engineering from Clemson University. During the PhD his dissertation and research was focused on design and analysis of collaborative freight logistics network including intermodal networks and cross-dock logistics. He is currently working as a Sr. Operations Research Specialist with BNSF Railway and his work involves optimization of intermodal hub operations. His scientific interests are intermodal transportation, freight logistics, and collaborative logistics.
William G. Ferrell Jr
William G. Ferrell Jr is the Fluor Professor of Industrial Engineering at Clemson University. His current research interests are in collaborative logistics and, especially, their implementation in hyperconnected systems of multimodal transportation and facilities.
Nathan Huynh
Nathan Huynh is the Director of the Nebraska Transportation Center and the Keith W. Klaasmeyer Professor of Civil and Environmental Engineering at the University of Nebraska-Lincoln. His current research interests include logistics, Intermodal freight terminal design and operations, connected and coordinated multimodal systems, infrastructure resiliency, and transportation equity. He received his B.S. degree in Civil and Environmental Engineering from Temple University, and both his M.S. and Ph.D. degrees in transportation engineering from The University of Texas at Austin.
Bhavya Padmanabhan
Bhavya Padmanabhan is currently a Ph.D. student at the University of South Carolina, Department of Civil and Environmental Engineering. She received her master's degree in Transportation Engineering from the College of Engineering Guindy, Anna University. She earned her bachelor's degree in Civil Engineering from TKM College of Engineering, Kerala University. Her research focuses on supply chain, logistic collaboration, and freight network optimization.