Hierarchical earthquake shelter planning in urban areas: A case for Shanghai in China

Proper pre-disaster emergency shelter locations and the corresponding victim allocation contribute to mitigating disaster loss in densely populated urban areas. The number of victims and their needs in emergency shelters change over the duration of the post-earthquake period, as evidenced by both actual earthquake records and theoretical analysis. To match the time-varying demand with the shelter planning, the hierarchical shelters that provide different level services should be projected. We first estimate the varying number of the victims in shelters during the post-earthquake period, and then model the locations for emergency shelters with a nested hierarchy, and also model the allocation of victims among shelters. Furthermore, we employ an efficient hybrid cross-entropy method to solve the location model and develop a better victim allocation scheme with a swap move to overcome the drawbacks of other allocation schemes. The empirical results from application to the Xuhui District in Shanghai of China show that emergency shelter planning based on a time-varying demand can reduce the construction cost of shelters and the averaged evacuation distance traveled by the victims, compared to the current policy based on the unvarying demand.