Risk–Failure Interactive Propagation and Recovery of Sea–Rail Intermodal Transportation Network Considering Recovery Propagation

Existing research concentrates on analyzing the propagation and recovery of complex network risk or failure under a single model, which makes it difficult to effectively deal with the chain reaction. Concerning the recovery delay caused by the risk–failure interactions, this paper proposes a model for the propagation and recovery of risk–failure interactions. This model not only considers the network risk–failure interactive propagation mechanism but also introduces the load-balancing strategy and repair mechanism. The study quantifies the impact of the station on network resilience after different attack modes. In addition, the resilience metrics based on the station failure are established to accurately represent the resilience evolution of the network during propagation and recovery. Finally, focusing on the Belt and Road transportation network, we explore the evolution of network resilience under the variation of failure station repair time, station risk state recovery rate, and hub station allocation parameters. The simulation results showed that the model reduced the resilience loss through resilience recovery and accelerated the network back to normal in the face of attacks, shortening the station repair time and increasing the station risk recovery rate significantly improved the overall resilience level of the network, and increasing the proportion of hub station balancing based on the residual capacity effectively improved the minimum resilience of the sea–rail intermodal transportation network.