基于弹复性的交通网络应急恢复阶段策略优化.

Recovery from major disasters is generally divided into an emergency recovery phase and a comprehensive recovery phase. The former faces multiple difficulties such as limits of time, funds and resources. The traditional research of post-disaster recovery of transportation networks lacks targeted research that combines the characteristics of the emergency recovery phase. To address these problems, a resilience-based optimization model of the recovery strategy in the emergency recovery phase for transportation networks is proposed. Firstly, two resilience metrics are proposed to measure resilience from both the recovery rapidity and the cumulative loss of network performance. Then, considering the interaction between system resilience at the upper level and user behavior at the lower level, a bi-level programming model for the transportation network recovery strategy in the emergency recovery phase is established. A special interactive bi-level algorithm is designed by combining the algorithm for the parallel machine scheduling problem and the algorithm for the user equilibrium problem. Finally, the validity of the proposed model is verified by a case study. The results indicate that the proposed model and algorithm can effectively determine the optimal recovery strategy in the emergency recovery phase for large-scale transportation networks with constraints of resources, funds, recovery goals, decision maker preference, etc. [ABSTRACT FROM AUTHOR]