Multi-objective Particle Swarm Optimization Algorithm Based on Gaussian-Cauchy Mixture Mutation
SHU Yiming
DAI Yiru
Abstract：Aiming at the defects of poor convergence performance,insufficient global search ability and easy to fall into local optimization in MOPSO optimization algorithm for solving complex multi-objective optimization problems,a multi-objective parti-cle swarm optimization algorithm based on Gaussian-Cauchy mixed mutation(GC-MOPSO)is proposed.The algorithm uses a muta-tion disturbance mechanism of mixed Gaussian mutation and Cauchy mutation to improve the local and global search ability of parti-cles,and uses the tournament selection mechanism to select the global optimal individual in the external file to increase the diversi-ty of the population.The advantages of the algorithm are verified by comparing with six other algorithms in anti-generation distance(IGD).
Keywords：multi-objective optimizationparticle swarm optimization algorithmGaussian-Cauchy variationtournament selection
Publication Date：2024-06-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1593-1597,1603 )