A novel model for quick response to disaster relief distribution

Abstract

This paper presents a hybrid fuzzy-optimization methodology to solve the large-scale disaster relief distribution problem with the main goal of minimizing the total number of fatalities. The proposed method mainly contains a three-stage operational algorithm. Here fuzzy clustering techniques are used in the first stage to classify the damaged areas based on respective relief demand attributes and priority, followed by the second and the third stage, where fuzzy linear programming is employed to deal with the situation when the demand for victims is greater than the available resources. Results of a numerical study are illustrated to demonstrate the applicability of the proposed method.