广东电力Issue(10)：32-37,6.DOI:10.3969/j.issn.1007-290X.2014.10.007
基于自动重组机制的多目标粒子群优化算法研究
Multi-obj ect Particle Swarm Optimization Based on Automatic Reorganization Mechanism
摘要
Abstract
Aiming at premature convergence of particle swarm optimization,a kind of automatic reorganization mechanism was proposed.When detecting premature convergence of particle swarm,it was able to automatically trigger position reor-ganization and consequently liberate particle swarm in partial optimization and make it back to the right path of searching for global optimum.In addition,establishment of the new searching space after particle swarm reorganization would be on the basis of uncertainty degree of deviation between position of the particle and global optimum position.Meanwhile,ac-cording to a certain proportion,a new searching range was able to be acquired.Experimental results indicated that in bench-mark testing applying two-dimension Rastrigin function,this optimization algorithm was able to acquire approximate global optimum solution.关键词
进化算法/粒子群优化/多目标优化/过早收敛/自动重组机制Key words
improved algorithm/particle swarm optimization/multi-object optimization/premature convergence/auto-matic reorganization mechanism分类
信息技术与安全科学引用本文复制引用
袁靖,袁丹,彭道刚,张浩..基于自动重组机制的多目标粒子群优化算法研究[J].广东电力,2014,(10):32-37,6.基金项目
上海市“科技创新行动计划”高新技术领域重点科研项目(14511101200) （14511101200）
