关键词: 紧急疏散, 选址&mdash, 路径优化, 混合遗传算法, 公共交通, 不确定性优化

Abstract: This paper presents an optimization modeling technique to develop an evacuation plan for transit-dependent residents during in the event of natural disaster such as the emergency hurricane situation. The transit evacuation operation problem is formulated as a class of location-routing problem (LRP) with uncertain demands. The objective function is set to minimize the total evacuation time. The LRP problem identifies the optimal serving areas and transit vehicle routings to move evacuees from the flooding affected zone to designated shelters or safe destinations. The computational experience is presented on the application of hybrid genetic algorithms, artificial neural network, and hill climbing heuristic algorithms. Numerical experiments are conducted using the real survey data from Gulfport, MS, to illustrate the proposed modeling technique. Experimental results show that the hybrid GA performs well both in quality and efficiency than traditional GA.

Key words: emergency evacuation, location-routing problem, hybrid genetic algorithm, public transit, uncertain optimization