Optimizing Locations and Scales of Emergency Warehouses Based on Damage Scenarios

Choosing the locations and the capacities of emergency warehouses for the storage of relief materials is critical to the quality of services provided in the wake of a large-scale emergency such as an earthquake. This paper proposes a stochastic programming model to determine disaster sites’ locations as well as their scales by considering damaged scenarios of the facility and by introducing seismic resilience to describe the ability of disaster sites to resist earthquakes. The objective of the model is to minimize fixed costs of building emergency warehouses, expected total transportation costs under uncertain demands of disaster sites and penalty costs for lack of relief materials. A local branching (LB) based solution method and a particle swarm optimization (PSO) based solution method are proposed for the problem. Extensive numerical experiments are conducted to assess the efficiency of the heuristic according to the real data of Yunnan province in China.