An Improved Particle Swarm Optimization Algorithm and Its Application for Solving Traveling Salesman Problem
Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.649
An improved particle swarm optimization (IPSO) algorithm was proposed. In the basic particle swarm optimization (PSO) algorithm, the tentative behavior of individuals and the mutation of velocity have been introduced, according to the law of evolutionary process. Using the single node adjustment algorithm, each particle searches the neighbor area by itself at every generation after general steps. In the evolution, the particles can escape from the local optimum with the mutation of velocity. This kind of enhanced study behavior accords with the biological natural law even more, and helps to find the global optimum solution with great chance. For solving traveling salesman problem, numerical simulation results for the benchmark TSP problems shows the effectiveness and efficiency of the proposed method.
PSO, IPSO, TSP
Wei Xiong, Jiang-wei Zhang, "An Improved Particle Swarm Optimization Algorithm and Its Application for Solving Traveling Salesman Problem", Computer Science and Information Engineering, World Congress on, vol. 04, no. , pp. 612-616, 2009, doi:10.1109/CSIE.2009.649