An improved tabu search for solving symmetric traveling salesman problems

Tabu search (TS) is a heuristic for providing excellent solutions to hard combinatorial problems. However, the quality of solutions of TS depends on the initial solution. In this paper, we proposed an improved TS approach for solving symmetric traveling salesman problems (TSP). The proposed algorithm is an integration of two heuristic approaches which are TS and simulated annealing (SA). The algorithm was tested on five chosen benchmarked problems of symmetric TSP. The performance of the proposed algorithm is compared with that of the conventional TS algorithm in order to validate the quality of solutions. Computational results and comparisons show that the proposed algorithm has better performance than that of the conventional TS.