Modeling the Optimal Emergency Routing and Evacuation of the Urban Transport Network

Natural disasters often bring about wide-ranging catastrophic consequences. The post-crisis assessment of different regions generally indicates poor crisis management, evacuation routing, and planning performance, leading to incoordination and wasting time and network capacity. Therefore, this study presented an integrated solution to determine evacuation routes in a short time using an algorithm based on network analysis and the definition of safe nodes and arcs based on crisis conditions. The proposed flow optimization model employs the MCNFP method to find the shortest evacuation routes from each node to the safe zone and guide the maximum possible flow through this route. The model's efficiency was controlled using 12 small networks with different combinations of nodes and vehicles and 10 medium networks with different numbers of nodes and similar demands. Then, the running times of each MCNFP algorithm and the proposed model (P-M) were compared. The results showed that the evacuation time increased by increasing the number of nodes and the routing expanse and complexity. In addition, increasing the number of vehicles in limited and local networks increased the evacuation time. Generally, the research results confirmed the optimal speed of the proposed algorithm in network evacuation.