Optimal stochastic inventory-distribution strategy for damaged multi-echelon humanitarian logistics network

The quick distribution of relief goods is vital in alleviating human suffering in affected areas. A relief strategy that delivers (pushes) goods to the affected population depending on the predicted demand is critical, especially during the early post-disaster period when accurate demand information is lacking. Several inventory-distribution strategies based on multi-echelon humanitarian logistics networks have been previously investigated to facilitate a quick response to demand information. However, natural disasters have raised doubts about the performance of these networks. This paper presents the disaster conditions under which conventional multi-echelon networks are conducive to push-mode strategies that deliver relief goods depending on the predicted demand. Specifically, an approximate solution to the optimal inventory-distribution strategy is analytically derived from a dynamic stochastic optimization problem using deterministic approximation and decomposition. Several numerical validations ensure the optimality and practical applicability of the strategy. The approximate strategy identifies disaster conditions that do not contribute to push-mode strategies in conventional multi-echelon networks and proposes an alternative network structure.