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Recovery Strategies for Urban Rail Transit Network Based on Comprehensive Resilience

Author

Listed:
  • Mingming Zheng

    (School of Traffic and Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

  • Hanzhang Zuo

    (School of Environment and Chemical Engineering, Dalian Jiaotong University, Dalian 116028, China)

  • Zitong Zhou

    (School of Traffic and Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China)

  • Yuhan Bai

    (Zhejiang Haining Rail Transit Operation Management Co., Jiaxing 314411, China)

Abstract

To enhance the resilience of urban rail transit networks in dealing with interference events and facilitating rapid network recovery, this paper focuses on studying damaged urban rail transit networks and proposes comprehensive resilience evaluation indexes for urban rail transit networks that take into account two dimensions: network topology and passenger travel path selection. A bi-level programming model is constructed to maximize the comprehensive toughness, where the upper-level model is an integer planning model for determining the optimal recovery sequence of the affected stations under interference events that result in station closure or inoperability. The lower-level model is a passenger flow allocation model aiming to minimize travelers’ impedance. A genetic algorithm and Dijkstra’s labeling algorithm are used to solve the upper model as well as the shortest path of the lower model, respectively. Using a real-world urban rail transit network as an example, this research applies different recovery strategies, random recovery, node importance-based recovery, and comprehensive toughness-based recovery, across five common interference scenarios to analyze the recovery sequence of stations in each scenario. The modeling results show that the comprehensive toughness-based restoration strategy yields the most favorable results for the rail transportation network, followed by the node importance-based restoration strategy. In addition, the network’s toughness varies more significantly when employing different restoration strategies during target interference, as compared to the random and range interference scenarios.

Suggested Citation

  • Mingming Zheng & Hanzhang Zuo & Zitong Zhou & Yuhan Bai, 2023. "Recovery Strategies for Urban Rail Transit Network Based on Comprehensive Resilience," Sustainability, MDPI, vol. 15(20), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:15018-:d:1262359
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    References listed on IDEAS

    as
    1. Ma, Zhiao & Yang, Xin & Wu, Jianjun & Chen, Anthony & Wei, Yun & Gao, Ziyou, 2022. "Measuring the resilience of an urban rail transit network: A multi-dimensional evaluation model," Transport Policy, Elsevier, vol. 129(C), pages 38-50.
    2. Stefano Starita & Maria Paola Scaparra, 2018. "Passenger railway network protection: a model with variable post-disruption demand service," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(4), pages 603-618, April.
    3. Jungyeol Hong & Reuben Tamakloe & Soobeom Lee & Dongjoo Park, 2019. "Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    4. C. von Ferber & T. Holovatch & Yu. Holovatch & V. Palchykov, 2009. "Public transport networks: empirical analysis and modeling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 68(2), pages 261-275, March.
    5. 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.
    6. Qiaoyun Yang & Dan Yang & Peng Li & Shilu Liang & Zhenghu Zhang & Guangdong Wu, 2021. "Resilient City: A Bibliometric Analysis and Visualization," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-17, May.
    7. Nan, Cen & Sansavini, Giovanni, 2017. "A quantitative method for assessing resilience of interdependent infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 35-53.
    8. Sarhadi, Hassan & Tulett, David M. & Verma, Manish, 2017. "An analytical approach to the protection planning of a rail intermodal terminal network," European Journal of Operational Research, Elsevier, vol. 257(2), pages 511-525.
    9. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    10. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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