Stochastic Optimization for Humanitarian Logistics: Pre-positioning and Multi-period Distribution of Relief Supplies

Large-scale natural disasters result in significant human casualties and economic losses. Effective disaster management strategies require the strategic pre-positioning of relief supplies before a disaster and the rapid distribution of these supplies to affected regions afterward. In this paper, we propose a novel stochastic programming model that integrates the pre-positioning and multi-period distribution of relief supplies in humanitarian logistics. The model takes into account uncertainties related to relief supply demand, potential damage to pre-positioned supplies at relief facilities, and vulnerabilities in the road infrastructure. To assess the practical utility of our model, we conduct a real-world case study based on the earthquakes in Ya’an, China. The results demonstrate the model’s effectiveness in aiding decision-makers to optimize both pre-positioning and distribution strategies for relief supplies.