Improvement of Particle Swarm Algorithm and Its Application in Optimization Function
MA Famin
ZHANG Lin
WANG Jinbiao
Abstract：The defection of particle swarm optimization algorithm means that an increase in iterations decreases swarm diversity and causes prematurity,thus probably producing local optimization results.However,immune mechanism of biology is capable of effectively overcoming these shortcomings.Firstly particle swarm algorithm is organically combined with immune principle to form immune particle swarm optimization algorithm (IMPSO),then certain improvements will be made in inertia coefficient and learning factor of PSO algorithm and finally effect of algorithm improvement will be verified through calculation of typical optimization function.
Keywords：particle swarm optimization algorithmimmune theoryimmune particle swarm optimization algorithminertia coefficientlearning factor
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：5( 1252-1255,1293 )