مشخصات پژوهش

In this paper a multi-objective location-routing problem with capacitated vehicles is presented. The proposed model considers vehicles’ traveled distances, service time and waiting time while guarantees that the sum of these parameters be lower than a predetermined value. Two objective functions are investigated. First objective function is minimizing the total cost of the system and the second one is minimizing the gap between the vehicles’ traveled distances. A Multi-Objective Imperialist Competitive Algorithm (MOICA) is developed to solve the problem. The great efficiency of the MOICA is demonstrated via comparing with a famous meta-heuristics, named Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). Several crossover and mutation strategies are adjusted for each algorithm based on response surface methodology. The results, in terms of two well-known comparison metrics, indicate that the proposed MOICA outperforms NSGA-II.