Metaheuristic Optimization for Logistics in Natural Disasters

Logistics in natural disasters or emergencies involve highly complicated optimization problems with diverse characteristics. The contribution of the present paper is twofold. First, it introduces a multi-period model aiming to minimize the shortages of different relief products in a number of affected areas. The relief products are transported via multiple modes of transportation from dispatch centers to these areas, while adhering to traffic restrictions. A test suite of benchmark problems with diverse characteristics is generated from the proposed model and solved to optimality with CPLEX. The test suite is used for benchmarking a number of established metaheuristics. Necessary modifications are introduced in the algorithms, in order to fit the special requirements of the specific problem type. The algorithms’ performance is assessed in terms of solution accuracy with respect to the optimal solutions. Comparisons among the employed metaheuristics offer valuable insight regarding their ability to tackle humanitarian logistics problems.