Research on resilience-based road network restoration rescheduling considering secondary disasters

This paper studies highway network repair rescheduling under secondary disasters from a resilience perspective. It analyzes the time-evolution of network performance during disasters and defines highway network resilience using average network efficiency. Resilience is evaluated by two indicators, i.e., performance resilience and recovery speed resilience. The concept of repair rescheduling is introduced to adjust repair plans after secondary disasters. Based on this framework, a repair scheduling model under single disasters and a rescheduling model under secondary disasters are established. The former maximizes performance resilience, while the latter maximizes both performance resilience and recovery speed resilience. Both models consider constraints on repair funds, the number of repaired sections, and repair teams. A genetic algorithm solves the single-disaster model, and a hybrid genetic algorithm solves the rescheduling model. In a case study, the models and algorithms are applied to verify feasibility, and complex network topological indicators evaluate the repair plans. This study is significant for rapidly restoring highway network resilience, ensuring efficient emergency relief transport, and promoting rapid economic recovery in disaster-stricken areas.