Disaster relief logistics under demand-supply incongruence environment: A sequential approach

Abstract Several logistics problems involving disaster relief have attracted growing research interest in the recent decade. A commonality among these problems is that demand–supply incongruence is always observed in post-disaster logistics operations due to the limited relief supplies and the randomly increasing relief demands. In such situations, the decision maker fails to meet the total relief demands simultaneously. This study employs a novel decision-making framework, where the traditional disaster relief logistics actions (e.g., vehicles routing and relief allocation) are replaced by periodic, sequential actions involving demand point location and assignment. A sequential approach allows the decision maker, in the face of every demand-point, to decide whether to locate and assign it to relief suppliers immediately or later, which sequentially influences the decision in the next period. A dynamic optimization model is built and solved by using particle swarm optimization algorithm. The results of a case study indicate the advantages of the sequential approach.