| 陈伟栋,童华刚,郜振华,张洪亮.一种改进的多目标人工蜂群算法[J].南华大学学报(自然科学版),2017,31(2):56~61.[CHEN Wei-dong,TONG Hua-gang,GAO Zhen-hua,ZHANG Hong-liang.Improved Multi-objective Artificial Bee Colony Algorithm[J].Journal of University of South China(Science and Technology),2017,31(2):56~61.] |
| 一种改进的多目标人工蜂群算法 |
| Improved Multi-objective Artificial Bee Colony Algorithm |
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| DOI： |
| 中文关键词: 人工蜂群算法 多目标优化问题 自适应搜索 变异操作 |
| 英文关键词:artificial bee colony algorithm multi-objective optimization problem adaptive search variation operation |
| 基金项目:安徽省教育厅人文社科重点项目(SK2016A0168);安徽省社科联社会科学创新发展课题(A2015070) |
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| 中文摘要: |
| 由于基本多目标人工蜂群算法存在着种群盲目搜索、算法开发能力有限等缺点,在利用人工蜂群算法求解多目标优化问题时,提出了一种改进的人工蜂群算法.通过在算法中引入自适应搜索机制和变异机制等操作,使得种群个体可以有针对性地进行更新,同时也大大提高了种群个体的多样性.最后利用几种多目标的测试函数对改进前后的多目标人工蜂群算法的性能进行测试,结果表明:改进后多目标人工蜂群算法具有良好的算法收敛性和均匀性. |
| 英文摘要: |
| In the use of artificial colony algorithm to solve multi-objective optimization problems,the standard multi-objective artificial colony algorithm has some shortcomings,such as population blind search,limited algorithmic development capability and so on.An improved artificial colony algorithm is proposed in this paper,which introduces the adaptive algorithm search mechanism and the mechanism of variation operation to make the individual species be targeted for updates and improve the diversity of population greatly.Finally several kinds of multi-objective test function are used to verify the standard and improved multi-objective artificial colony algorithm performance,the comparison result indicates the improved multi-objective artificial colony algorithm has better convergence and uniformity. |
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