Solving the Traveling Salesman Problem by an Efficient Hybrid Metaheuristic Algorithm

The traveling salesman problem (TSP) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. The TSP is probably the most famous and extensively studied problem in the field of combinatorial optimization. Because this problem is an NP-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. So, an efficient hybrid metaheuristic algorithm called ICATS is proposed in this paper. The first stage of the ICATS is to solve the TSP by the imperialist competitive algorithm (ICA), and then the TS is used for improving solutions. This process avoids the premature convergence and makes better solutions. Computational results on several standard instances of TSP show efficiency of the proposed algorithm compared with the genetic algorithm (GA), bee colony optimization (BCO), and particle swarm optimization (PSO).