Optimizing disaster relief goods distribution and transportation: a mathematical model and metaheuristic algorithms

Abstract

The effective distribution of relief goods is critical in mitigating the impact of natural disasters and preserving human life. This study addresses a relief goods distribution problem, assuming the existence of multiple relief orders that must be delivered to various disaster-stricken regions from a network of warehouses using a fleet of diverse vehicles. The objective is to identify the most suitable warehouse for each relief order, allocate relief orders to vehicles, batch the orders in the designated vehicles, and devise routing plans to minimize the total delivery time. A mixed-integer linear programming model is formulated to tackle this problem. Owing to the problem’s NP-hard nature, a metaheuristic algorithm, known as the Multiple League Championship Algorithm, is developed. Furthermore, two innovative variants of the MLCA , namely the League Base Multiple League Championship Algorithm (L- MLCA) and the Playoff Multiple League Championship Algorithm (P-MLCA), are introduced.Experimental results indicate that the P-MLCA outperforms the other two algorithms. The solutions derived from the P-MLCA are compared with the optimal solutions obtained by a commercial solver for small-scale problems. This comparative analysis demonstrates the promising performance of the P-MLCA in finding the optimal distribution of relief goods.