A modified particle swarm optimization algorithm
QIAN Wei-yi
ZHANG Xun
Abstract：Particle swarm optimization algorithm (PSO) is a heuristic algorithm based on bionic technology,To solve the premature convergence problem of the Particle Swarm Optimization, a modified PSO algorithm was proposed.In this algorithm, A new mutation operator with the exploration and exploitation ability is proposed to avoid falling into local optimal solutions.Based on the new mutation operator, a new updating formula of particle position is proposed.According to the system stability theory, the area of parameters of the modified algorithm is given.Finally, A performance test of benchmark functions is taken to confirm convergence speed and solution precision of the modified algorithm.The experimental results show that the modified algorithm has faster convergence speed and higher solution precision.
Keywords：particle swarm optimization algorithmmutation operatorstabilityfunction optimization
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 97-103 )