Title :
Improved Enhanced Self-Tentative PSO algorithm for TSP
Author :
Zhang, Jiang-wei ; Si, Wen-jian
Author_Institution :
Sch. of Comput. Sci. & Technol., Xuchang Univ., Xuchang, China
Abstract :
This paper proposes an Improved Enhanced Self-Tentative (IEST) particle swarm optimization (PSO) algorithm for solving TSP problem. The improved method can easily solve the cross problem for the tour, and greatly increased the chances to find the better solution in the evolutionary process. Time complexity of the improved method was analyzed, based on this the proper parameters was set to solve different benchmark TSP problems, numerical simulation results show the effectiveness and efficiency of the proposed method.
Keywords :
computational complexity; evolutionary computation; particle swarm optimisation; travelling salesman problems; enhanced self-tentative PSO algorithm; evolutionary process; particle swarm optimization; time complexity; travelling salesman problem; Algorithm design and analysis; Benchmark testing; Cities and towns; Clustering algorithms; Particle swarm optimization; Traveling salesman problems; improved enhanced self-tentative; pso; tsp;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583011
