Abstract
The correct location of earthquake emergency shelters and their allocation to residents can effectively reduce the number of casualties by providing safe havens and efficient evacuation routes during the chaotic period of the unfolding disaster. However, diverse and strict constraints and the discrete feasible domain of the required models make the problem of shelter location and allocation more difficult. A number of models have been developed to solve this problem, but there are still large differences between the models and the actual situation because the characteristics of the evacuees and the construction costs of the shelters have been excessively simplified. We report here the development of a multi-objective model for the allocation of residents to earthquake shelters by considering these factors using the Chaoyang district, Beijing, China as a case study. The two objectives of this model were to minimize the total weighted evacuation time from residential areas to a specified shelter and to minimize the total area of all the shelters. The two constraints were the shelter capacity and the service radius. Three scenarios were considered to estimate the number of people who would need to be evacuated. The particle swarm optimization algorithm was first modified by applying the von Neumann structure in former loops and global structure in later loops, and then used to solve this problem. The results show that increasing the shelter area can result in a large decrease in the total weighted evacuation time from scheme 1 to scheme 9 in scenario A, from scheme 1 to scheme 9 in scenario B, from scheme 1 to scheme 19 in scenario C. If the funding were not a limitation, then the final schemes of each scenario are the best solutions, otherwise the earlier schemes are more reasonable. The modified model proved to be useful for the optimization of shelter allocation, and the result can be used as a scientific reference for planning shelters in the Chaoyang district, Beijing.
Highlights
Increasing attention is being paid to the impacts of natural disasters on humans as both society and technology develop [1,2]
This study has introduced a multi-objective earthquake shelter allocation model by considering different evacuation scenarios using the Chaoyang district of Beijing as a case study
The particle swarm optimization (PSO) optimum algorithm was first modified by adding an outside loop and combing it with the simulated annealing (SA) algorithm and used to solve the problem
Summary
Increasing attention is being paid to the impacts of natural disasters on humans as both society and technology develop [1,2]. Based on a set covering model, Dalal et al [9] studied the selection of sites for typhoon shelters in the countryside by adding a capacity constraint and a distance constraint. Their model was solved by applying a clustering analysis method. Based on the capacitated-median model, and considering the different function of relief points in various levels and the connection between them, Widener [10] and Widener and Horner [11] developed a hierarchical capacitated-median model and applied it to the location-allocation problem of hurricane relief points in Leon county, Florida, USA. Considering the hierarchical location problems of China, Chen and You [12] divided the facility system into two levels, a basic level and an advanced level, and built a hierarchical location model
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