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Identification of critical nodes in multimodal transportation network

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  • Wang, Longjian
  • Zheng, Shaoya
  • Wang, Yonggang
  • Wang, Longfei

Abstract

A transportation network is an essential lifeline engineering system, and its reliability is critical when faced with natural or man-made disasters. The reliability of the transportation network will affect the decision-making process of the managers of a country or province during disasters. When a disaster strikes, one or more critical nodes in the transportation network may completely lose their basic function, which may greatly reduce the reliability of the transportation network. Therefore, identifying critical nodes in the transportation network is of utmost importance in the analysis of the reliability of the transportation network. The complex network theory provides a powerful tool to identify critical nodes. In this study, we propose an improved weighted k-shell (IWKS) model to identify the critical nodes based on the complex networks theory. This model comprehensively considers the diversity of the transportation modes, independent transportation ability, and connectivity of the node. Additionally, the comprehensive transportation network in Zhejiang (China) was used to illustrate the effectiveness of the proposed method. The results show that the proposed method can effectively identify critical nodes in the multimodal transportation network (MTN). We considered three indicators in this model, and it is also feasible to select a few more indicators. This study may provide a new perspective for the application of the complex network theory in the transportation system, and may also provide the necessary information to improve the reliability of the network.

Suggested Citation

  • Wang, Longjian & Zheng, Shaoya & Wang, Yonggang & Wang, Longfei, 2021. "Identification of critical nodes in multimodal transportation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    • Handle: RePEc:eee:phsmap:v:580:y:2021:i:c:s037843712100443x
    DOI: 10.1016/j.physa.2021.126170
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