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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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    as
    1. Kelly J. Cormican & David P. Morton & R. Kevin Wood, 1998. "Stochastic Network Interdiction," Operations Research, INFORMS, vol. 46(2), pages 184-197, April.
    2. Qi, Xiangtong & Bard, Jonathan F. & Yu, Gang, 2004. "Supply chain coordination with demand disruptions," Omega, Elsevier, vol. 32(4), pages 301-312, August.
    3. Nielsen, L.K. & Maróti, G., 2009. "Disruption Management of Rolling Stock in Passenger Railway Transportation," ERIM Report Series Research in Management ERS-2009-046-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Podofillini, Luca & Zio, Enrico & Vatn, Jørn, 2006. "Risk-informed optimisation of railway tracks inspection and maintenance procedures," Reliability Engineering and System Safety, Elsevier, vol. 91(1), pages 20-35.
    5. Johannes O. Royset & R. Kevin Wood, 2007. "Solving the Bi-Objective Maximum-Flow Network-Interdiction Problem," INFORMS Journal on Computing, INFORMS, vol. 19(2), pages 175-184, May.
    6. Jin Y. Yen, 1971. "Finding the K Shortest Loopless Paths in a Network," Management Science, INFORMS, vol. 17(11), pages 712-716, July.
    7. Rocco S., Claudio M. & Emmanuel Ramirez-Marquez, José & Salazar A., Daniel E., 2010. "Bi and tri-objective optimization in the deterministic network interdiction problem," Reliability Engineering and System Safety, Elsevier, vol. 95(8), pages 887-896.
    8. Richard Wollmer, 1964. "Removing Arcs from a Network," Operations Research, INFORMS, vol. 12(6), pages 934-940, December.
    9. Burdett, R.L. & Kozan, E., 2009. "Techniques for inserting additional trains into existing timetables," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 821-836, September.
    10. G Zhu & J F Bard & G Yu, 2005. "Disruption management for resource-constrained project scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(4), pages 365-381, April.
    11. Qi, Xiangtong & Bard, Jonathan F. & Yu, Gang, 2006. "Disruption management for machine scheduling: The case of SPT schedules," International Journal of Production Economics, Elsevier, vol. 103(1), pages 166-184, September.
    12. Abril, M. & Barber, F. & Ingolotti, L. & Salido, M.A. & Tormos, P. & Lova, A., 2008. "An assessment of railway capacity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 774-806, September.
    13. Michael Francis Gorman, 1998. "An application of genetic and tabu searches to the freight railroad operating plan problem," Annals of Operations Research, Springer, vol. 78(0), pages 51-69, January.
    14. Crainic, Teodor Gabriel, 2000. "Service network design in freight transportation," European Journal of Operational Research, Elsevier, vol. 122(2), pages 272-288, April.
    15. Alberto Caprara & Matteo Fischetti & Paolo Toth, 2002. "Modeling and Solving the Train Timetabling Problem," Operations Research, INFORMS, vol. 50(5), pages 851-861, October.
    16. Lawley, Mark & Parmeshwaran, Vijay & Richard, Jean-Philippe & Turkcan, Ayten & Dalal, Malay & Ramcharan, David, 2008. "A time-space scheduling model for optimizing recurring bulk railcar deliveries," Transportation Research Part B: Methodological, Elsevier, vol. 42(5), pages 438-454, June.
    17. Lars-Göran Mattsson, 2007. "Railway Capacity and Train Delay Relationships," Advances in Spatial Science, in: Alan T. Murray & Tony H. Grubesic (ed.), Critical Infrastructure, chapter 7, pages 129-150, Springer.
    18. Kohl, Niklas & Larsen, Allan & Larsen, Jesper & Ross, Alex & Tiourine, Sergey, 2007. "Airline disruption management—Perspectives, experiences and outlook," Journal of Air Transport Management, Elsevier, vol. 13(3), pages 149-162.
    19. Burdett, R.L. & Kozan, E., 2006. "Techniques for absolute capacity determination in railways," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 616-632, September.
    20. Steven K. Peterson & Richard L. Church, 2008. "A Framework for Modeling Rail Transport Vulnerability," Growth and Change, Wiley Blackwell, vol. 39(4), pages 617-641, December.
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    Cited by:

    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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