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An improved particle swarm optimization (IPSO) algorithm is proposed for solving traveling salesman problem (TSP) which is a well-known NP-complete problem. Based on the different experimental results, this paper analysis the parameters influences to the algorithm optimization ability. The IPSO algorithm can get a better global optimum in multiple TSP problems by setting the proper parameters. Numerical simulation results for the different scale benchmark TSP problems show the effectiveness and efficiency of the proposed method using the proper parameters.