This work develops a multi-objective, two-stage stochastic, non-linear, and mixed-integer mathematical model for relief pre-positioning in disaster management. Improved imbalance and efficacy measures incorporated into the model based on a new utility level of the delivered relief commodities. Moreover, this model considers the usage possibility of a set of alternative routes for each of applied transportation modes and consequently improves the network reliability. An integrated separable programming-augmented εconstraint approach is proposed to address the problem. The best Pareto-optimal solution is selected by PROMETHEE-II. Finally, the theoretical improvements of the presented approach are validated by experiments and a real case study.
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