Optimizing temporary rescue facility locations for large-scale urban environmental emergencies to improve public safety

Abstract

Emergency rescue facility is an important component of urban system and affects public safety. Due to the special characteristics and complex environment of large-scale environmental disasters in urban areas, locations of emergency rescue facilities should be optimized. This study proposed an innovative methodological framework to optimize the locations of emergency rescue facility in the case of large-scale urban environmental disasters. A decision optimization model which consists of three-objectives representing service capacity, global efficiency and equity was developed. An appropriate spatial representation and encoding strategy was designed and coupled with the NSGA-II algorithm for model solving. Based on a hypothetical disaster scenario, a case study of Chaoyang district in Beijing is presented to demonstrate the methodology and explore the conflicting objectives. The results provide evidence that the model is able to successfully generate the Pareto-optimal frontier for the multi-objective emergency facility location problem, and provide a pool of alternative solutions to the decision-makers. The findings show that the framework proposed in this study has the potential to be a useful decision support tool for urban planning with respect to public safety.