Determining the location of earthquake emergency shelters and the allocation of affected population to them are key issues that face shelter planning and emergency management. To solve this emergency shelter location...Determining the location of earthquake emergency shelters and the allocation of affected population to them are key issues that face shelter planning and emergency management. To solve this emergency shelter location–allocation problem, evacuation time and the construction cost of shelters—both influenced by the evacuation population size and its spatial distribution—are two important considerations. In this article, a mathematical model with two objectives—to minimize total weighted evacuation time(TWET) and total shelter area(TSA)—is allied with a modified particle swarm optimization algorithm to address the problem. The relationships between evacuation population size, evacuation time, and total shelter area are examined using Jinzhan Town in Chaoyang District of Beijing, China, as a case study. The results show that TWET has a power function relationship with TSA under different population size scenarios, and a linear function applies between evacuation population and TWET under different TSAs. The joint relationships of TSA, TWET, and population size show that TWET increases with population increase and TSA decrease, and compared with TSA, population influences TWET more strongly. Given a reliable projection of population change and spatial planning of a study area, this method can be useful for government decision making on the location of earthquake emergency shelters and on the allocation of evacuees to those shelters.展开更多
基金funded by the Ministry of Science and Technology, China (Grant Number: 2016YFA0602404)Ministry of Education and State Administration of Foreign Experts Affairs, China (Grant Number: B08008)National Natural Science Foundation of China (Grant Number: 41201547)
文摘Determining the location of earthquake emergency shelters and the allocation of affected population to them are key issues that face shelter planning and emergency management. To solve this emergency shelter location–allocation problem, evacuation time and the construction cost of shelters—both influenced by the evacuation population size and its spatial distribution—are two important considerations. In this article, a mathematical model with two objectives—to minimize total weighted evacuation time(TWET) and total shelter area(TSA)—is allied with a modified particle swarm optimization algorithm to address the problem. The relationships between evacuation population size, evacuation time, and total shelter area are examined using Jinzhan Town in Chaoyang District of Beijing, China, as a case study. The results show that TWET has a power function relationship with TSA under different population size scenarios, and a linear function applies between evacuation population and TWET under different TSAs. The joint relationships of TSA, TWET, and population size show that TWET increases with population increase and TSA decrease, and compared with TSA, population influences TWET more strongly. Given a reliable projection of population change and spatial planning of a study area, this method can be useful for government decision making on the location of earthquake emergency shelters and on the allocation of evacuees to those shelters.
