| 一种基于模糊学习子群的多目标粒子群算法 |
| |
| 引用本文： | 江勋林,郭坚毅,唐建,凌海风.一种基于模糊学习子群的多目标粒子群算法[J].计算机应用研究,2011,28(12):4492-4494. |
| |
| 作者姓名： | 江勋林 郭坚毅 唐建 凌海风 |
| |
| 作者单位： | 1. 解放军理工大学工程兵工程学院,南京,210007
2. 南京军区73602部队,南京,210007 |
| |
| 摘 要： | 为提高多目标粒子群算法的局部搜索能力,提出了一种模糊学习子群多目标粒子群算法(FLSMOP-SO).在搜索过程中,每个粒子模糊自适应学习生成不确定的p个粒子形成一个子群而不是只产生一个新粒子,然后在其中选择模糊满意解作为其下一代新粒子.对四个典型测试函数的实验结果表明,新算法比NSGAⅡ和MOPSO两种经典多目标优化算法有显著的优越性.
|
| 关 键 词： | 多目标粒子群算法 模糊学习 自适应子群 |
Multi-objective particle swarm algorithm based on fuzzy-learning sub-swarm |
| |
| JIANG Xun-lin,GUO Jian-yi,TANG Jian,LING Hai-feng.Multi-objective particle swarm algorithm based on fuzzy-learning sub-swarm[J].Application Research of Computers,2011,28(12):4492-4494. |
| |
| Authors: | JIANG Xun-lin GUO Jian-yi TANG Jian LING Hai-feng |
| |
| Affiliation: | JIANG Xun-lin1,GUO Jian-yi2,TANG Jian1,LING Hai-feng1(1.Engineering Institute of Engineering Corp,PLA University of Science & Technology,Nanjing 210007,China,2.No.73602 Unit,Nanjing Military Region,China) |
| |
| Abstract: | To improve the local search ability of the MOPSO,this paper put forward a new fuzzy learning sub-swarm multi-objective particle swarm optimization(FLSMOPSO).In the searching process,each particle in the swarm could have linear regressive p particles by self-adaptive learning to form a sub-warm rather than a single particle.Then selected a fuzzy satisfied solution particle as the new position of the particle.Comparative analysis to the two typical algorithm shows that the new algorithm have prominent advanta... |
| |
| Keywords: | multi-objective particle swarm algorithm fuzzy-learning self-adaptive sub-swarm |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《计算机应用研究》浏览原始摘要信息 |
|
点击此处可从《计算机应用研究》下载全文 |
|
