Emergency transportation planning in disaster relief supply chain management: a cooperative fuzzy optimization approach

Emergency transportation is the most important part of disaster relief supply chain operations, and its planning problem always involves multiple objectives, complex constraints, and inherent uncertainty. Based on the analysis of several natural disaster that occurred in China since 2007, we propose a multi-objective fuzzy optimization problem of emergency transportation planning in disaster relief supply chains, which takes into consideration three transportation modes: air, rail, and road. To cope with the uncertainty, we employ three correlated fuzzy ranking criteria, and define the beta dominance relation for evaluating the solutions of the problem. To efficiently solve the problem, we develop a cooperative optimization method that divides the integrated problem into a set of subcomponents, evolves the sub-solutions concurrently, and brings together the sub-solutions to construct complete solutions. The proposed method is effective, scalable, and robust, and thus contributes greatly to the performance of emergency transportation planning in disaster management.