An Improved Hybrid Particle Swarm Optimization Algorithm for Solving Traveling Salesman Problem
PEI Haochen
LOU Yuansheng
YE Feng
HUANG Qian
Abstract：In order to improve the convergence speed and accuracy of the particle swarm optimization(PSO)algorithm in solv-ing the traveling salesman problem(TSP),an improved hybrid particle swarm optimization(IHPSO)algorithm is proposed.Based on existing hybrid particle swarm optimization algorithm,the greedy crossover operator is used to improve the convergence speed, and a chaotic particle is introduced into the population by using the characteristics of chaotic motion.Instead of searching for the op-timal solution in the solution space,the chaotic particle is used to implement greedy cross with other particles,and then expand the search scope of other particles,so the method can be utilized to enhance the precision of the solution.By using MATLAB,the exper-iments are carried out on the data set in TSPLIB,and the experimental results show that the improved algorithm can improve both convergence speed and accuracy.
Keywords：particle swarm optimizationgreedy crossoverchaotic particletraveling salesman problem
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 218-221,235 )