An interactive approach for designing a robust disaster relief logistics network with perishable commodities

Abstract

Pre-positioning of relief commodities in appropriate locations and quantities at a pre-disaster phase assists a disaster relief logistics network in order to efficiently distribute the commodities to demand points; however, a disaster may occur after a long time, and generally perishable commodities (e.g., medical commodities and packed milk) have a fixed lifetime for use. Hence, this paper aims at developing a new integrated model in order to determine the optimum location-allocation and distribution plan, along with the best ordering policy for renewing the stocked perishable commodities at the pre-disaster phase. The uncertain nature of the problem leads to the utilization of a scenario-based robust stochastic approach. The proposed model simultaneously seeks to minimize: (1) the average of the weighted response times and (2) the total operational cost at the pre-disaster phase and the penalty costs of unmet demand and unused commodities at a post-disaster phase. The reservation level Tchebycheff procedure (RLTP) as an interactive approach is also applied to cope with the presented bi-objective model. The significance of the presented model and the efficiency of the RLTP method are then tested via a real case study in Iran.