Based on the improved enhanced self-tentative (IEST) particle swarm optimization (PSO) algorithm, 2-opt local searching algorithm is introduced in the later evolution stage. 2-opt method further strengthen the self-tentative and make up the deficiency of the IEST PSO algorithm and solve the cross solution problem. The hybrid PSO algorithm greatly increases the chances to find the better solution in the evolutionary process. Time complexity of the 2-opt method is analyzed. Based on this the proper parameters is set to solve different benchmark TSP problems, numerical simulation results show the effectiveness and efficiency of the hybrid PSO algorithm.
Xiaohu ShiYuan ZhouLincong WangQi WangYanchun Liang
Morad BouzidiMohammed Essaid Riffi
Guillermo Cabrera‐GuerreroSilvana RONCAGLIOLO D.Juan P. RIQUELMEClaudio CubillosRicardo Soto
A. K. M. Foysal AhmedJi Ung Sun