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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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    6. Huizhu Wang & Jianqin Zhou, 2023. "Location of Railway Emergency Rescue Spots Based on a Near-Full Covering Problem: From a Perspective of Diverse Scenarios," Sustainability, MDPI, vol. 15(8), pages 1-16, April.
    7. 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).
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    9. 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.
    10. 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).
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