Scenario-Based Multi-Objective Optimum Allocation Model for Earthquake Emergency Shelters Using a Modified Particle Swarm Optimization Algorithm: A Case Study in Chaoyang District, Beijing, China

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.

Site Selection Models in Natural Disaster Shelters: A Review

“…Hu et al [52] developed an earthquake shelter location-allocation model, with the objectives of minimizing the total distance from communities to shelters and the total cost, and solved it using a genetic algorithm. Zhao et al [53,54] introduced an earthquake shelter allocation model, with the objectives of minimizing the total weighted evacuation time and the total area of shelters, and solved it using a modified PSO algorithm combined with the SA algorithm. Zhou et al [55] proposed a multiobjective urban shelter location planning model, which comprehensively considered the principles of fairness and efficiency in the location selection by integrating the maximum coverage model and the p-median model.…”

Relationships Between Evacuation Population Size, Earthquake Emergency Shelter Capacity, and Evacuation Time

“…The particle swarm optimum (PSO) algorithm is one of the popular optimization heuristics for solving complex problems in many fields, such as in computer science (Yin et al 2007) and the social sciences (Cai et al 2014), and it has been applied to solve the problems of facility selection (Ghaderi et al 2012), redundancy allocation (Yeh 2009), and location routing (Marinakis and Marinaki 2008). The algorithm has also been used to solve earthquake disaster shelter location and allocation problems by adding multiple objectives, strict constraints, and discrete feasible domains (Hu et al 2012;Zhao et al 2015). Thus, in this study, the modified PSO algorithm proposed by Zhao et al (2015) is used to solve the shelter location problem.…”

“…The algorithm has also been used to solve earthquake disaster shelter location and allocation problems by adding multiple objectives, strict constraints, and discrete feasible domains (Hu et al 2012;Zhao et al 2015). Thus, in this study, the modified PSO algorithm proposed by Zhao et al (2015) is used to solve the shelter location problem.…”

“…Most recently, Xu et al (2018) provided a hybrid bilevel model for earthquake emergency shelter location and allocation by considering the dynamic number of evacuees and its implementation, and the model results were also compared with the ones from multiple objective models. Optimization heuristics algorithms have been introduced to solve these models due to the complexity of the location problem (Li et al 2009;Hu et al 2012Hu et al , 2014Zhao et al 2015) that cannot be solved by traditional mathematical methods.…”

“…This model minimizes total weighted evacuation time (TWET) and total shelter area (TSA) and considers a number of scenarios. Second, the model is solved using a modified particle swarm optimum (PSO) method (Zhao et al 2015), and the relationships between various factors are analyzed and suggestions about how to use the results are given.…”