Multiobjective Site Selection Model for Emergency Shelter Facilities in Urban Areas
Abstract Industrial and economic development is primarily applied to densely populated urban areas. If a sudden disaster occurs in such areas, the consequences can be severe. Shelter facility location affects the implementation of postdisaster relief work. This study explored residents’ perceived utility of evacuation time, their risk utility for road blocking, and the cost factors associated with constructing shelter facilities in the context of governance. A location model for emergency shelter facilities in cities was established on the basis of the aforementioned factors. Because the resolution of the random-weighted genetic algorithm (RWGA) is susceptible to influence from random weights, a robustness random-weighted method (RRWM) was developed. The validity and feasibility of the location model were examined through numerical analysis. Finally, the convergence of the RRWM was analyzed and compared with that of the RWGA and a single-objective genetic algorithm. The results revealed that the proposed algorithm exhibited satisfactory performance and can assist in evaluation and decision-making related to the selection of urban shelter facility locations.