Evaluating the Importance of Metro Network Stations Based on CRITIC-VIKOR: A Case Study of Xi’an City

After the disturbance occurs in metro operation, the recovery sequence of different stations has a critical impact on the efficiency of the metro operation. In order to determine the importance of the metro stations, this paper selects importance evaluation indicators from three aspects: network connectivity, network structure, and node nature. First, we conduct correlation analysis on nine evaluation indicators to determine the significance of each evaluation indicator, then use the CRITIC-VIKOR method to comprehensively evaluate the failure stations, and simulate them in the Xi’an metro network, ranking the evaluated stations based on their importance. The results show that there are differences in the key sites identified by different indicators: the sites identified based on the maximum network subgraph and the changes in network efficiency are mainly located on the loop line and outer radiating lines of the loop and adjacent loops. The stations identified based on degree centrality, intermediate centrality, and node nature are mainly transfer stations. The stations identified based on change in service efficiency are mainly those with large passenger flow. The network center area is mainly identified based on tight centrality and Eigenvector centrality. The result indicates that the current structure distribution of the Xi’an urban network is uneven, and there are too many isolated sections of the loop line radiating outward. Therefore, it is necessary to strengthen the connection and transportation of multiple lines. The importance of evaluation results can be used as the recovery order of Xi’an metro stations in case of emergencies.

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Published
2024-12-11
DOI
https://doi.org/10.1061/9780784485484.115
Citations
1
Primary Topic
Evaluation Methods in Various Fields
Type
article
Field-Weighted Citation Impact
0.92
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Evaluating the Importance of Metro Network Stations Based on CRITIC-VIKOR: A Case Study of Xi’an City

Min Yan, Ying Ma, Zhaodong Liu, Yonggang Wang et al.
1 citations
Evaluation Methods in Various Fields
0.92
article

Evaluating the Importance of Metro Network Stations Based on CRITIC-VIKOR: A Case Study of Xi’an City

Min Yan, Ying Ma, Zhaodong Liu, Yonggang Wang, Kun Yang
article en
1 citations

Abstract

After the disturbance occurs in metro operation, the recovery sequence of different stations has a critical impact on the efficiency of the metro operation. In order to determine the importance of the metro stations, this paper selects importance evaluation indicators from three aspects: network connectivity, network structure, and node nature. First, we conduct correlation analysis on nine evaluation indicators to determine the significance of each evaluation indicator, then use the CRITIC-VIKOR method to comprehensively evaluate the failure stations, and simulate them in the Xi’an metro network, ranking the evaluated stations based on their importance. The results show that there are differences in the key sites identified by different indicators: the sites identified based on the maximum network subgraph and the changes in network efficiency are mainly located on the loop line and outer radiating lines of the loop and adjacent loops. The stations identified based on degree centrality, intermediate centrality, and node nature are mainly transfer stations. The stations identified based on change in service efficiency are mainly those with large passenger flow. The network center area is mainly identified based on tight centrality and Eigenvector centrality. The result indicates that the current structure distribution of the Xi’an urban network is uneven, and there are too many isolated sections of the loop line radiating outward. Therefore, it is necessary to strengthen the connection and transportation of multiple lines. The importance of evaluation results can be used as the recovery order of Xi’an metro stations in case of emergencies.

Chang'an University (CN)
Sustainable cities and communities
Openalex Percentile: Top 14%
Evaluation Methods in Various Fields
0.92
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