Multi-objective particle swarm optimization

doi:10.3778/j.issn.1002-8331.2008.34.018

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (34): 64-66.DOI: 10.3778/j.issn.1002-8331.2008.34.018

• 理论研究 • Previous Articles Next Articles

Multi-objective particle swarm optimization

WANG Hong-gang,MA Liang,LI Gao-ya

Business School，University of Shanghai for Science and Technology，Shanghai 200093，China

Received:2007-12-19 Revised:2008-03-05 Online:2008-12-01 Published:2008-12-01
Contact: WANG Hong-gang

多目标微粒群优化算法

王洪刚,马良,李高雅

上海理工大学管理学院，上海 200093

通讯作者: 王洪刚

Abstract

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 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.

Key words: multi-objective optimization, Pareto solutions, particle swarm optimization

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。

关键词: 多目标优化, Pareto解集, 微粒群算法

WANG Hong-gang,MA Liang,LI Gao-ya. Multi-objective particle swarm optimization[J]. Computer Engineering and Applications, 2008, 44(34): 64-66.

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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Multi-objective particle swarm optimization

多目标微粒群优化算法

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