| 多目标微粒群优化算法 |
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| 引用本文： | 王洪刚,马良,李高雅.多目标微粒群优化算法[J].计算机工程与应用,2008,44(34):64-66. |
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| 作者姓名： | 王洪刚 马良 李高雅 |
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| 作者单位： | 上海理工大学 管理学院，上海 200093 |
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| 基金项目： | 上海市重点学科建设资助项目 |
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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。
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| 关 键 词： | 多目标优化 Pareto解集 微粒群算法 |
| 收稿时间： | 2007-12-19 |
| 修稿时间： | 2008-3-5
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Multi-objective particle swarm optimization |
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| WANG Hong-gang,MA Liang,LI Gao-ya.Multi-objective particle swarm optimization[J].Computer Engineering and Applications,2008,44(34):64-66. |
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| Authors: | WANG Hong-gang MA Liang LI Gao-ya |
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| Affiliation: | Business School，University of Shanghai for Science and Technology，Shanghai 200093，China |
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| Abstract: | 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 optimiza-tion 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. |
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| Keywords: | multi-objective optimization Pareto solutions particle swarm optimization |
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