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A scenario model for enhancing the resilience of an urban rail transit network by adding new links

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  • Yin, Yong
  • Chen, Jinqu
  • Chen, Zhuo
  • Du, Bo
  • Li, Baowen

Abstract

Adding new links to an existing urban rail transit (URT) network helps improve its operations by shortening passenger travel time under normal operations and disruptions. However, only a few studies have considered the impact of uncertain disruption occurrence stations on URT network design. This paper addresses this gap by proposing and solving a scenario model for determining the optimal scheme for adding new links to an existing URT network while considering the uncertainty of disruption occurrence stations. Numerical experiments are conducted on the Chengdu subway system to verify the effectiveness of the proposed model. Results indicate that disruptions occurring at a station result in an average performance loss of 0.61%. The scheme for adding new links obtained from this model helps improve network performance under normal operations and disruptions. The cumulative improved normal operating performance during the entire day and the ratio of improved weighted resilience metric are 1.638 and 24.59%, respectively. The solution of the proposed model is greatly affected by several parameters such as the total length of new links. Some useful suggestions for guiding URT network extensions are proposed based on the results of the sensitivity analysis of the above parameters.

Suggested Citation

  • Yin, Yong & Chen, Jinqu & Chen, Zhuo & Du, Bo & Li, Baowen, 2024. "A scenario model for enhancing the resilience of an urban rail transit network by adding new links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
  • Handle: RePEc:eee:phsmap:v:637:y:2024:i:c:s0378437124000918
    DOI: 10.1016/j.physa.2024.129583
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    1. T. L. Magnanti & R. T. Wong, 1984. "Network Design and Transportation Planning: Models and Algorithms," Transportation Science, INFORMS, vol. 18(1), pages 1-55, February.
    2. Farahani, Reza Zanjirani & Miandoabchi, Elnaz & Szeto, W.Y. & Rashidi, Hannaneh, 2013. "A review of urban transportation network design problems," European Journal of Operational Research, Elsevier, vol. 229(2), pages 281-302.
    3. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    4. Canca, David & De-Los-Santos, Alicia & Laporte, Gilbert & Mesa, Juan A., 2019. "Integrated Railway Rapid Transit Network Design and Line Planning problem with maximum profit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 1-30.
    5. Guihaire, Valérie & Hao, Jin-Kao, 2008. "Transit network design and scheduling: A global review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1251-1273, December.
    6. Linyuan Lü & Yi-Cheng Zhang & Chi Ho Yeung & Tao Zhou, 2011. "Leaders in Social Networks, the Delicious Case," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-9, June.
    7. Jin, Kun & Wang, Wei & Li, Xinran & Chen, Siyuan & Qin, Shaoyang & Hua, Xuedong, 2023. "Cascading failure in urban rail transit network considering demand variation and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    8. Lebing Wang & Jian Gang Jin & Gleb Sibul & Yi Wei, 2023. "Designing Metro Network Expansion: Deterministic and Robust Optimization Models," Networks and Spatial Economics, Springer, vol. 23(1), pages 317-347, March.
    9. Jicun Zhang & Jiyou Fei & Xueping Song & Jiawei Feng, 2021. "An Improved Louvain Algorithm for Community Detection," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-14, November.
    10. Laporte, Gilbert & Mesa, Juan A. & Perea, Federico, 2010. "A game theoretic framework for the robust railway transit network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 447-459, May.
    11. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    12. Li, Qian & Zhou, Tao & Lü, Linyuan & Chen, Duanbing, 2014. "Identifying influential spreaders by weighted LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 47-55.
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