IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6613-d1122844.html
   My bibliography  Save this article

Research on the Performance Recovery Strategy Model of Hangzhou Metro Network Based on Complex Network and Tenacity Theory

Author

Listed:
  • Xiaohong Yin

    (School of Economics and Management, Liaoning University of Technology, Jinzhou 121001, China)

  • Jiakun Wu

    (School of Economics and Management, Liaoning University of Technology, Jinzhou 121001, China)

Abstract

Based on complex networks and resilience theory, the structural characteristics and post-disaster performance recovery process of the urban metro network are studied to determine the best repair strategy for metro network performance under different scenarios. Specifically: (1) The space-L method is used to model the Hangzhou metro network, and MATLAB software is used to calculate the characteristic parameter values of the Hangzhou metro network structure; (2) A model of the post-disaster resilience of the Hangzhou metro network was constructed, and network efficiency was used as the evaluation index of the resilience level and resilience of the metro network; (3) The performance recovery process of the metro network under different scenarios was simulated and the optimal recovery strategy of the post-disaster metro network was obtained. The results show that the degree values of the Hangzhou metro network nodes are all generally low; the average passage path between nodes is long and the nodes are scattered, which makes the convenience of residents’ travel low. In addition, the degree index and the betweenness have some influence on the recovery order of the failed nodes. Finally, the genetic algorithm solves the post-disaster optimal recovery strategy of the metro network with good results.

Suggested Citation

  • Xiaohong Yin & Jiakun Wu, 2023. "Research on the Performance Recovery Strategy Model of Hangzhou Metro Network Based on Complex Network and Tenacity Theory," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6613-:d:1122844
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6613/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/8/6613/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elisa Frutos Bernal & Angel Martín del Rey, 2019. "Study of the Structural and Robustness Characteristics of Madrid Metro Network," Sustainability, MDPI, vol. 11(12), pages 1-24, June.
    2. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Fauzan Hanif Jufri & Jun-Sung Kim & Jaesung Jung, 2017. "Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event," Energies, MDPI, vol. 10(11), pages 1-17, November.
    3. Yang, Bofan & Zhang, Lin & Zhang, Bo & Xiang, Yang & An, Lei & Wang, Wenfeng, 2022. "Complex equipment system resilience: Composition, measurement and element analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    4. Francis, Royce & Bekera, Behailu, 2014. "A metric and frameworks for resilience analysis of engineered and infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 90-103.
    5. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    6. 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.
    7. Ruiying Li & Qiang Dong & Chong Jin & Rui Kang, 2017. "A New Resilience Measure for Supply Chain Networks," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    8. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    9. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    10. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    11. Li, Ruiying & Gao, Ying, 2022. "On the component resilience importance measures for infrastructure systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 36(C).
    12. Ottenburger, Sadeeb Simon & Çakmak, Hüseyin Kemal & Jakob, Wilfried & Blattmann, Andreas & Trybushnyi, Dmytro & Raskob, Wolfgang & Kühnapfel, Uwe & Hagenmeyer, Veit, 2020. "A novel optimization method for urban resilient and fair power distribution preventing critical network states," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
    13. Mühlhofer, Evelyn & Koks, Elco E. & Kropf, Chahan M. & Sansavini, Giovanni & Bresch, David N., 2023. "A generalized natural hazard risk modelling framework for infrastructure failure cascades," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    14. Geng, Sunyue & Liu, Sifeng & Fang, Zhigeng, 2021. "Resilient communication model for satellite networks using clustering technique," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Barker, Kash & Moronta, Jose, 2018. "Quantifying the resilience of community structures in networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 466-474.
    16. MacKenzie, Cameron A. & Hu, Chao, 2019. "Decision making under uncertainty for design of resilient engineered systems," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    17. Araceli Zavala & David Nowicki & Jose Emmanuel Ramirez-Marquez, 2019. "Quantitative metrics to analyze supply chain resilience and associated costs," Journal of Risk and Reliability, , vol. 233(2), pages 186-199, April.
    18. Zhang, Chao & Xu, Xin & Dui, Hongyan, 2020. "Resilience Measure of Network Systems by Node and Edge Indicators," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    19. Woodard, Mark & Marashi, Koosha & Sedigh Sarvestani, Sahra & Hurson, Ali R., 2021. "Survivability evaluation and importance analysis for cyber–physical smart grids," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    20. Nicholson, Charles D. & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 62-73.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6613-:d:1122844. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.