计算机与数字工程2024，Vol.52Issue(6)：1593-1597,1603,6.DOI:10.3969/j.issn.1672-9722.2024.06.001
基于高斯-柯西混合变异的多目标粒子群算法
Multi-objective Particle Swarm Optimization Algorithm Based on Gaussian-Cauchy Mixture Mutation
摘要
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).关键词
多目标优化/粒子群优化算法/高斯-柯西变异/锦标赛选择Key words
multi-objective optimization/particle swarm optimization algorithm/Gaussian-Cauchy variation/tournament selection分类
信息技术与安全科学引用本文复制引用
舒一鸣,戴毅茹..基于高斯-柯西混合变异的多目标粒子群算法[J].计算机与数字工程,2024,52(6):1593-1597,1603,6.基金项目
上海市自然科学基金项目"考虑技术内生演变的能源-经济-环境系统集成模型研究"(编号:19ZR1461500)资助. （编号:19ZR1461500）
