Research On Decision Optimization For Resilience Restoration Of Post-disaster Highway Networks

The road network plays a crucial role in the transportation of people and goods.However,due to its relatively centralized network structure,extensive coverage,and complex geographical environment,the road network is particularly vulnerable to natural disasters such as floods,earthquakes,and typhoons.The destruction caused by such disasters can result in a significant reduction in the level of road network service,hindering economic development and impeding timely rescue and disaster relief efforts.Thus,it is essential to restore the damaged road network promptly following a disaster.This article proposes a resilience-based optimization method for decision-making during the emergency recovery phase of the road network.The study first analyzes the dynamic change curve of the road network under natural disasters and introduces the concept of road network resilience.Through a comparative analysis of resilience and related evaluation indicators such as reliability,fragility,and robustness,the differences and connections between them are revealed.The study also evaluates the road network’s resilience under natural disasters from two aspects: connectivity resilience and repair speed resilience.Furthermore,a comprehensive road network recovery scheduling optimization model is constructed to maximize the connectivity resilience and repair speed resilience of the road network,while considering multiple constraint conditions such as repair fund constraints,repair team quantity constraints,and maximum acceptable repair period constraints.A hybrid discrete particle swarm algorithm is used to solve this optimization problem and find the best road network repair plan.Finally,a case study is conducted to verify the feasibility and effectiveness of the proposed road network performance evaluation system and post-disaster road network repair model.The results demonstrate that the proposed approach not only provides a comprehensive idea for post-disaster road network recovery but also offers scientific decision support to decision-makers.