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多目标微粒群优化算法 被引量：5

Multi-objective particle swarm optimization
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摘要 通过设计一种Pareto解集过滤器,并在此基础上给出多目标优化条件下的微粒群算法群体停滞判断准则,基于该准则提出了一种多目标微粒群优化算法。算法利用Pareto解集过滤器提高了候选解的多样性,并使用图形法将所提算法与经典的多目标优化进化算法在一组标准测试函数上进行了比较,结果表明算法具有更好的搜索效率。 A new kind of filter for Pareto solutions is presented.And a kind of critertion judging the stagnation of the particles in particle swarm optimization based on the filter is proposed.Based on which,a kind of multi-objective particle swarm optimization algorithm is proposed.By using the filter for Pareto solutions can improve algorithm＇s ability to keep diversity.The proposed algorithm is compared with some well known multi-objective evolutionary algorithms through series of standard test functions by means of visual graphs.The results indicate that the algorithm can search the Pareto optimum more effectively.
作者 王洪刚 马良 李高雅
机构地区 上海理工大学管理学院
出处 《计算机工程与应用》 CSCD 北大核心 2008年第34期64-66,207,共4页 Computer Engineering and Applications
基金 上海市重点学科建设资助项目(No.T0502)
关键词 多目标优化 PARETO解集 微粒群算法 multi-objective optimization Pareto solutions particle swarm optimization
分类号 O22 [理学—运筹学与控制论]
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参考文献7

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二级参考文献9

  • 1刘淳安,王宇平.一种基于新的模型的多目标存档遗传算法[J].计算机工程与应用,2005,41(4):43-45. 被引量：4
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共引文献4

同被引文献146

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二级引证文献49

计算机工程与应用
2008年 第34期

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