Using Tabu List and Several Local search Algorithms in Order to Improve the Imperialist Competitive Algorithm

One of the most important groups of heuristic algorithms is meta-heuristic algorithms which has been received much attention in recent years. Since these approaches are very efficient for escaping local optimum points, they are one of the best algorithms for solving operation research problems. This paper proposes a hybrid imperialist competitive algorithm called (IICA) in which a tabu list and several local search algorithms including the 1–0 exchange moves, the 1–1 exchange move and the 2-Opt move are used for improving performance of ICA. Furthermore, some of traveling salesman problems as one of the most important versions of the vehicle routing problem are considered for comparing this algorithm with other mataheuristic algorithms. Computational results on 13 standard benchmark problem instances show that the proposed algorithm is comparable in terms of solution quality to the other meta-heuristic algorithms