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Increasing the resilience level of a vulnerable rail network: The strategy of location and allocation of emergency relief trains

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  • Bababeik, Mostafa
  • Khademi, Navid
  • Chen, Anthony

Abstract

This paper examines the optimal location and allocation of relief trains (RTs) to enhance the resilience level of the rail network. Unlike probabilistic approaches, the priority of demand is handled by link exposure measure which considers the operational attributes of links and accessibility to road system. We formulate the proposed model using a bi-objective programming and solve it using an augmented e-constraint method (AUGMECON) combined with a fuzzy-logic approach. The proposed framework is employed to a real-world case study, and analytical results reveal the superiority of the proposed model in providing an economical and effective layout compared to conventional maximal covering model.

Suggested Citation

  • Bababeik, Mostafa & Khademi, Navid & Chen, Anthony, 2018. "Increasing the resilience level of a vulnerable rail network: The strategy of location and allocation of emergency relief trains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 110-128.
    • Handle: RePEc:eee:transe:v:119:y:2018:i:c:p:110-128
    DOI: 10.1016/j.tre.2018.09.009
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    Cited by:

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    2. Huizhu Wang & Jianqin Zhou & Ling Zhou, 2024. "A Lattice Boltzmann Method-like Algorithm for the Maximal Covering Location Problem on the Complex Network: Application to Location of Railway Emergency-Rescue Spot," Mathematics, MDPI, vol. 12(2), pages 1-20, January.
    3. Peng, Xiaoshuai & Zhang, Lele & Thompson, Russell G. & Wang, Kangzhou, 2023. "A three-phase heuristic for last-mile delivery with spatial-temporal consolidation and delivery options," International Journal of Production Economics, Elsevier, vol. 266(C).
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    5. Knoester, Max J. & Bešinović, Nikola & Afghari, Amir Pooyan & Goverde, Rob M.P. & van Egmond, Jochen, 2024. "A data-driven approach for quantifying the resilience of railway networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
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    10. Jing Zuo & Mengxing Shang & Jianwu Dang, 2022. "Research on the Optimization Model of Railway Emergency Rescue Network Considering Space-Time Accessibility," Sustainability, MDPI, vol. 14(21), pages 1-14, November.
    11. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    12. Yunfang Ma & Jose M. Sallan & Oriol Lordan, 2024. "Rail Transit Networks and Network Motifs: A Review and Research Agenda," Sustainability, MDPI, vol. 16(9), pages 1-21, April.
    13. Zhang, Li & Chen, Tingting & Liu, Zhongshan & Yu, Bin & Wang, Yunpeng, 2024. "Analysis of multi-modal public transportation system performance under metro disruptions: A dynamic resilience assessment framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    14. Hong, Wei-Ting & Clifton, Geoffrey & Nelson, John D., 2022. "Rail transport system vulnerability analysis and policy implementation: Past progress and future directions," Transport Policy, Elsevier, vol. 128(C), pages 299-308.
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    16. Xiaoge Zhang & Sankaran Mahadevan & Kai Goebel, 2019. "Network Reconfiguration for Increasing Transportation System Resilience Under Extreme Events," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 2054-2075, September.

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