Evacuation shelter and route selection based on multi-objective optimization approach

Abstract

Evacuation shelter and route selection are indispensable parts of emergency planning. An efficient plan can effectively evacuate people from a dangerous place to a safer location. Meanwhile, it is crucial to improve risk management. This article presents a multi-objective optimization algorithm based on social media and GIS to optimize shelter usage and personnel distribution considering social relationship. The proposed algorithm is examined using a case study for the Zhongguancun district in Beijing. The district is modeled by the graph theory. Traffic route data and population distribution are synthesized to form a risk map. Furthermore, the Floyd-Warshall algorithm is adopted to find a shortest path route in order to relocate evacuees to a safer place effectively. Efficiency, fairness and social relation are taken into consideration in this context.