Author(s)

Kuo-Chi Yen^*, Wu-Chiao Shih, Wei Chang

Department of Logistics Management, National Defense University, Taipei City.

Industrial and economic development primarily occurs in densely populated urban areas in Taiwan. The outbreak of war in such areas could have severe consequences. Disaster relief and homeland defense efforts are affected by the location of wartime shelters. This study explored the perceived utility of the evacuation time, the risk-utility of road blocking, and the cost factors associated with constructing shelters related to governance. A location model for wartime shelters in cities was established on the basis of these factors. Because random weights can affect the resolution of a random-weighted genetic algorithm (RWGA), a robust random-weighted method (RRWM) was developed. The validity and feasibility of the location model were examined through numerical analysis. The convergence of the RRWM was analyzed and compared with that of the RWGA and a single-objective genetic algorithm. The results indicate that the proposed algorithm exhibits satisfactory performance and can facilitate evaluation and decision-making related to the selection of urban shelter locations during wartime.

Location Problem, Multiobjective Programming, Wartime Shelter

Yen, K. , Shih, W. and Chang, W. (2023) Multiobjective Site Selection Model for Wartime Shelters in Urban Areas. Current Urban Studies, 11, 521-542. doi: 10.4236/cus.2023.113027.