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Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application

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  • Gedik, Ridvan
  • Medal, Hugh
  • Rainwater, Chase
  • Pohl, Ed A.
  • Mason, Scott J.

Abstract

In this paper, we present a two-stage mixed integer programming (MIP) interdiction model in which an interdictor chooses a limited amount of elements to attack first on a given network, and then an operator dispatches trains through the residual network. Our MIP model explicitly incorporates discrete unit flows of trains on the rail network with time-variant capacities. A real coal rail transportation network is used in order to generate scenarios to provide tactical and operational level vulnerability assessment analysis including rerouting decisions, travel and delay costs analysis, and the frequency of interdictions of facilities for the dynamic rail system.

Suggested Citation

  • Gedik, Ridvan & Medal, Hugh & Rainwater, Chase & Pohl, Ed A. & Mason, Scott J., 2014. "Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 45-57.
    • Handle: RePEc:eee:transe:v:71:y:2014:i:c:p:45-57
    DOI: 10.1016/j.tre.2014.06.017
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    1. Ivanov, Dmitry & Pavlov, Alexander & Pavlov, Dmitry & Sokolov, Boris, 2017. "Minimization of disruption-related return flows in the supply chain," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 503-513.
    2. Mostafa Bababeik & Mohammad Mahdi Nasiri & Navid Khademi & Anthony Chen, 2019. "Vulnerability evaluation of freight railway networks using a heuristic routing and scheduling optimization model," Transportation, Springer, vol. 46(4), pages 1143-1170, August.
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    7. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    8. Zhang, Ying & Qi, Mingyao & Lin, Wei-Hua & Miao, Lixin, 2015. "A metaheuristic approach to the reliable location routing problem under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 90-110.
    9. Zeng, Lanyan & Liu, Shi Qiang & Kozan, Erhan & Corry, Paul & Masoud, Mahmoud, 2021. "A comprehensive interdisciplinary review of mine supply chain management," Resources Policy, Elsevier, vol. 74(C).
    10. Majbah Uddin & Nathan Huynh, 2019. "Reliable Routing of Road-Rail Intermodal Freight under Uncertainty," Networks and Spatial Economics, Springer, vol. 19(3), pages 929-952, September.
    11. Darayi, Mohamad & Barker, Kash & Nicholson, Charles D., 2019. "A multi-industry economic impact perspective on adaptive capacity planning in a freight transportation network," International Journal of Production Economics, Elsevier, vol. 208(C), pages 356-368.
    12. Zhang, Ying & Snyder, Lawrence V. & Ralphs, Ted K. & Xue, Zhaojie, 2016. "The competitive facility location problem under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 453-473.
    13. Szymula, Christopher & Bešinović, Nikola, 2020. "Passenger-centered vulnerability assessment of railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 30-61.
    14. Jalali, Sajjad & Seifbarghy, Mehdi & Niaki, Seyed Taghi Akhavan, 2018. "A risk-averse location-protection problem under intentional facility disruptions: A modified hybrid decomposition algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 196-219.
    15. Ghorbani-Renani, Nafiseh & González, Andrés D. & Barker, Kash & Morshedlou, Nazanin, 2020. "Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    16. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    17. B. G. Tóth, 2021. "The effect of attacks on the railway network of Hungary," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 567-587, June.
    18. Márcio das Chagas Moura & Helder Henrique Lima Diniz & Enrique López Droguett & Beatriz Sales da Cunha & Isis Didier Lins & Vicente Ribeiro Simoni, 2017. "Embedding resilience in the design of the electricity supply for industrial clients," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-33, November.
    19. Woodburn, Allan, 2017. "The impacts on freight train operational performance of new rail infrastructure to segregate passenger and freight traffic," Journal of Transport Geography, Elsevier, vol. 58(C), pages 176-185.
    20. Ivanov, Dmitry & Pavlov, Alexander & Dolgui, Alexandre & Pavlov, Dmitry & Sokolov, Boris, 2016. "Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 7-24.
    21. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    22. Khademi, Navid & Babaei, Mohsen & Schmöcker, Jan-Dirk & Fani, Amirhossein, 2018. "Analysis of incident costs in a vulnerable sparse rail network – Description and Iran case study," Research in Transportation Economics, Elsevier, vol. 70(C), pages 9-27.

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