Functions optimization based on fast convergence particle swarm optimization
ZHENG Xiao-yue
Abstract：Aimed at the problem that the standard PSO algorithm was very sensitive to fall into the phenomenon of local minima and couldn′t escape,a new fast convergence PSO (FCPSO)algorithm based on balancing the diversity of location of individual particle was proposed.The algorithm introduced a new parameter,namely particle mean dimension was used to locate the global optimum solution fast and accurately.The experiment results showed that the convergence of the FCPSO algorithm was better than PSO algorithm and CPSO algo-rithm.
Keywords：particle swarm optimi-zation algorithmadap-tive weightconstriction factorparticle mean di-mension
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 89-92 )