基于两阶段鲁棒优化的铁路隧道应急资源调度研究OA

Railway tunnels have a closed environment and complex geological conditions.Emergencies such as fires and collapses are prone to triggering cascading disasters,posing severe challenges to the robustness of emergency resource scheduling.To address the shortcomings of existing rescue plans in addressing demand fluctuation and transportation time uncertainty,this paper proposed an emergency resource scheduling model based on two-stage robust optimization.The model divided the decision-making process into two stages:pre-disaster preventive resource allocation and post-disaster emergency dynamic scheduling.By introducing robustness coefficients and uncertainty sets,it systematically characterized the impact of multiple uncertain parameters and used the column and constraint generation algorithm for efficient solution.Simulation experiments were conducted by combining typical railway tunnel emergency scenarios.The robust scheduling scheme expands the path network to 8～9 routes with an average cost premium of 18.9%,significantly improving the risk resistance of the system,which verifies that the proposed method can ensure rescue efficiency while balancing economy and reliability.This paper not only provides a scientific decision support tool for emergency management of railway tunnels but also its method system can be extended to complex application scenarios such as multi-department collaborative rescue,which has high theoretical value and practical significance.