An integrated relief network design model under uncertainty: A case of Iran

In this study, a scenario-based robust approach is suggested for a multi-objective mixed-integer linear programming model in designing the relief network. A new approach to humanitarian inventory grouping problem based on the relief management objectives is proposed. The proposed model simultaneously optimizes inventory groups' number and corresponding service levels, assignment of relief commodities to groups, relief facility location, and relief service assignment. The proposed model aims to minimize the risk and the total cost of network management and simultaneously maximize the network population coverage. The fault tree analysis technique is used for vulnerability assessment of each demand point. To tackle the proposed optimization model, a hybrid Taguchi-based non-dominated sorting genetic algorithm-II is developed that incorporates an enhanced variable decomposition neighborhood search algorithm with fitness landscape analysis as its local search heuristic. The results illustrate the efficiency of the proposed model and solution algorithm in dealing with the considered disaster management issues.