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Rethinking critical node problem for railway networks from the perspective of turn-back operation

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  • Noguchi, Hiroki
  • Fuse, Masaaki

Abstract

Vulnerability assessment studies addressing the critical node problem for railway networks do not recognize the importance of turn-back operations as a typical reaction to disruption. The aim of this study is to explore the significance of turn-back operations during the process of identifying critical stations. This significance was quantified by comparing the results of critical stations (both with and without turn-back operations) in the Nagoya metro, Japan. The results indicate a large difference between critical stations identified with turn-back operations and those without. In addition, the criticality of stations without turn-backs tends to be underestimated. Our findings suggest that analysts and decision makers should rethink the critical node problem for railway networks from the perspective of turn-back operations.

Suggested Citation

  • Noguchi, Hiroki & Fuse, Masaaki, 2020. "Rethinking critical node problem for railway networks from the perspective of turn-back operation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    • Handle: RePEc:eee:phsmap:v:558:y:2020:i:c:s0378437120304969
    DOI: 10.1016/j.physa.2020.124950
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    Cited by:

    1. Hiroki Noguchi & Takuma Nishizawa & Masaaki Fuse, 2021. "A method to characterize the social cascading damage processes of disasters using media information," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(1), pages 231-247, May.
    2. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. Hou, Lei, 2022. "Network versus content: The effectiveness in identifying opinion leaders in an online social network with empirical evaluation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).

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