IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v71y2014icp45-57.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554514001124
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2014.06.017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.
    3. Bešinović, Nikola & Ferrari Nassar, Raphael & Szymula, Christopher, 2022. "Resilience assessment of railway networks: Combining infrastructure restoration and transport management," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    4. Zhixue Liu & Shukun Wang & Yanfeng Ouyang, 2017. "Reliable Biomass Supply Chain Design under Feedstock Seasonality and Probabilistic Facility Disruptions," Energies, MDPI, vol. 10(11), pages 1-18, November.
    5. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    6. Kirschstein, Thomas, 2018. "Rail transportation planning in the chemical industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 142-160.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Starita, Stefano & Scaparra, Maria Paola, 2016. "Optimizing dynamic investment decisions for railway systems protection," European Journal of Operational Research, Elsevier, vol. 248(2), pages 543-557.
    2. Smith, J. Cole & Song, Yongjia, 2020. "A survey of network interdiction models and algorithms," European Journal of Operational Research, Elsevier, vol. 283(3), pages 797-811.
    3. Chaya Losada & M. Scaparra & Richard Church & Mark Daskin, 2012. "The stochastic interdiction median problem with disruption intensity levels," Annals of Operations Research, Springer, vol. 201(1), pages 345-365, December.
    4. Li, Feng & Gao, Ziyou & Wang, David Z.W. & Liu, Ronghui & Tang, Tao & Wu, Jianjun & Yang, Lixing, 2017. "A subjective capacity evaluation model for single-track railway system with δ-balanced traffic and λ-tolerance level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 43-66.
    5. Cacchiani, Valentina & Furini, Fabio & Kidd, Martin Philip, 2016. "Approaches to a real-world Train Timetabling Problem in a railway node," Omega, Elsevier, vol. 58(C), pages 97-110.
    6. Talebian, Ahmadreza & Zou, Bo, 2015. "Integrated modeling of high performance passenger and freight train planning on shared-use corridors in the US," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 114-140.
    7. Endong Zhu & Teodor Gabriel Crainic & Michel Gendreau, 2014. "Scheduled Service Network Design for Freight Rail Transportation," Operations Research, INFORMS, vol. 62(2), pages 383-400, April.
    8. Claudio Contardo & Jorge A. Sefair, 2022. "A Progressive Approximation Approach for the Exact Solution of Sparse Large-Scale Binary Interdiction Games," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 890-908, March.
    9. Leonardo Lozano & J. Cole Smith, 2017. "A Backward Sampling Framework for Interdiction Problems with Fortification," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 123-139, February.
    10. Chen Li & Xiangtong Qi & Chung-Yee Lee, 2015. "Disruption Recovery for a Vessel in Liner Shipping," Transportation Science, INFORMS, vol. 49(4), pages 900-921, November.
    11. Pengfei Zhang & Neng Fan, 2017. "Analysis of budget for interdiction on multicommodity network flows," Journal of Global Optimization, Springer, vol. 67(3), pages 495-525, March.
    12. Dimitris Bertsimas & Ebrahim Nasrabadi & Sebastian Stiller, 2013. "Robust and Adaptive Network Flows," Operations Research, INFORMS, vol. 61(5), pages 1218-1242, October.
    13. Jabarzare, Ziba & Zolfagharinia, Hossein & Najafi, Mehdi, 2020. "Dynamic interdiction networks with applications in illicit supply chains," Omega, Elsevier, vol. 96(C).
    14. Burdett, RL, 2016. "Optimisation models for expanding a railway's theoretical capacity," European Journal of Operational Research, Elsevier, vol. 251(3), pages 783-797.
    15. Xiang, Yin, 2023. "Minimizing the maximal reliable path with a nodal interdiction model considering resource sharing," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    16. Juan S. Borrero & Leonardo Lozano, 2021. "Modeling Defender-Attacker Problems as Robust Linear Programs with Mixed-Integer Uncertainty Sets," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1570-1589, October.
    17. Laan, Corine M. & van der Mijden, Tom & Barros, Ana Isabel & Boucherie, Richard J. & Monsuur, Herman, 2017. "An interdiction game on a queueing network with multiple intruders," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1069-1080.
    18. Eli Towle & James Luedtke, 2018. "New solution approaches for the maximum-reliability stochastic network interdiction problem," Computational Management Science, Springer, vol. 15(3), pages 455-477, October.
    19. Coviello, Nicola, 2015. "Modelling periodic operations on single track lines: Timetable design and stability evaluation," Research in Transportation Economics, Elsevier, vol. 54(C), pages 2-14.
    20. Alice Paul & Susan E. Martonosi, 2024. "The all-pairs vitality-maximization (VIMAX) problem," Annals of Operations Research, Springer, vol. 338(2), pages 1019-1048, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:71:y:2014:i:c:p:45-57. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.