A Fuzzy Multi-Objective Model For Logistic Planning in Disaster Relief Operations

Disasters can cause many human casualties and considerable financial loss and destruction. this is mainly because of ineffective preventive measures, incomplete preparedness, and weak relief logistics systems. quick, effective and efficient post-catastrophic actions are of great importance for lowering the losses and casualties. a key element, is an efficient logistic plan for distributing needed relief commodities efficiently and fairly among the affected people. in this paper, we propose a fuzzy multi-objective, multi-modal, multi- commodity logistic model in emergency response to disaster occurrence. the aim of the proposed model is to assign limited resources equitably to the affected regions while minimizing transfer costs of commodities as well as distribution centers activation costs, and maximizing satisfied demand. in the proposed model, the optimal location of distribution centers among candidate points to receive people donations as well as sending and receiving different kinds of relief commodities are determined. the amount of voluntary donations is subject to uncertainty and are considered as fuzzy parameters. the number of victims immediately after disaster is also vague and is expressed as fuzzy demand. a case study is presented to investigate the properties of the optimization problem and justify the practical efficiency of the formulation.