站点失效下铁路客运网络韧性评估与恢复策略研究OA

To address the challenges of resilience assessment and post-failure recovery in railway pas-senger networks following large-scale station failures,this study proposes a railway passenger net-work resilience assessment and optimal recovery method based on a service efficiency indicator.First,from the perspectives of network service capacity and actual operational characteristics,a railway pas-senger service network model is constructed.A service efficiency indicator considering the number of operating trains between stations is proposed,and a network service resilience assessment model is es-tablished using the resilience curve and the service efficiency indicator.Second,an optimal resilience recovery model is formulated with the objective of maximizing recovery resilience,and an improved Particle Swarm Optimization(PSO)algorithm is developed to determine the optimal recovery strategy under large-scale station failures.Finally,the Chengdu-Chongqing railway passenger network is used as a case study to evaluate network resilience and compare the resilience recovery performance of dif-ferent strategies under three disturbance scenarios.The results indicate that the service efficiency indi-cator effectively assesses the impact of station failures on network performance and accurately identi-fies critical stations.The optimal recovery strategy derived from the resilience recovery model consis-tently outperforms both random and degree recovery strategies across all disturbance scenarios.Under deliberate attack scenarios,the recovery resilience of the network achieved by the optimal strategy im-proves by 69.90%and 4.81%compared with the random and degree recovery strategies,respectively.