| dc.description.abstract | Large-scale natural disasters result in significant human casualties and economic losses. Effective disaster management necessitates the strategic prepositioning of relief supplies before disasters and their swift distribution afterward. Different from prior studies that focused on single-period distribution with the objective of minimizing total costs, this paper presents a novel biobjective stochastic programming model that integrates prepositioning and multiperiod distribution of relief supplies in humanitarian logistics. The model concurrently aims to minimize overall costs and maximize transportation efficiency. We evaluate the model through a case study based on the Ya’an, China, earthquakes, demonstrating its effectiveness in optimizing relief supply strategies. Sensitivity analyses explore the impact of varying objective function weights, road capacity, and supply urgency, providing valuable managerial insights into humanitarian logistics decision-making. The insights gained from this study highlight the importance of proactive planning and strategic investment in infrastructure and logistics. By employing our biobjective stochastic programming model, decision-makers can develop robust strategies that balance cost and efficiency, ensuring a more effective and responsive disaster relief operation. | |
