A Three-Stage Relief Network Design Approach for Predictable Disasters Considering Time-Dependent Uncertainty

Relief network design for predictable disasters is a key issue in humanitarian logistics. However, existing studies on relief network design have not simultaneously considered multiple relief decision stages and the uncertainties which are reduced by improved forecast accuracy as a disaster approaches. These aspects are critical for efficient relief activities. The present study investigates a new relief network design problem for predictable disasters, especially typhoons, which have become increasingly frequent and severe in recent years. It integrates facility location decisions before any specific disaster warnings are issued, relief supply deployment and evacuation decisions between a warning and the onset of the disaster, and relief supply distribution decisions after a disaster strikes. This study also considers time-dependent uncertainties of the disaster's trajectory and intensity together. For the problem, a novel three-stage hybrid distributionally robust and robust optimization (3HDRO) model is proposed. To make it computationally tractable, the 3HDRO model is transformed into a deterministic equivalent (DE) model. A scenario-based decomposition heuristic algorithm is then designed to solve the DE model for large-scale instances. A case study of historical typhoons in Guangdong Province, China, is used to gain insights into the critical model parameters for disaster relief activities. Furthermore, experimental results on randomly generated instances demonstrate the effectiveness and efficiency of the proposed model and algorithm.