题名 | BSO20: efficient brain storm optimization for real-parameter numerical optimization |
作者 | |
通讯作者 | Luo,Wenjian |
发表日期 | 2021-10-01
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DOI | |
发表期刊 | |
ISSN | 2199-4536
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EISSN | 2198-6053
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卷号 | 7期号:5页码:2415-2436 |
摘要 | Brain storm optimization (BSO) is an emerging global optimization algorithm. The primary idea is to divide the population into different clusters, and offspring are generated within a cluster or between two clusters. However, the problems of inefficient clustering strategy and insufficient exploration exist in BSO. In this paper, a novel and efficient BSO is proposed, called BSO20 (proposed in 2020). BSO20 pays attention to both the clustering strategy and the mutation strategy. First, we propose a hybrid clustering strategy, which combines two clustering strategies, i.e., nearest-better clustering and random grouping strategy. The size of the subpopulation clustered by two strategies is dynamically adjusted as the population evolves. Second, a modified mutation strategy is used in BSO20 to share information within a cluster or among multiple clusters to enhance the ability of exploration. BSO20 is tested on the problems of the 2017 IEEE Congress on Evolutionary Computation competition on real parameter numerical optimization. BSO20 is compared with several variants of BSO and two variants of particle swarm optimization, and the experimental results show that BSO20 is competitive. |
关键词 | |
相关链接 | [Scopus记录] |
收录类别 | |
语种 | 英语
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学校署名 | 其他
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资助项目 | National Key Research and Development Program of China[2020YFB2104003];National Outstanding Youth Science Fund Project of National Natural Science Foundation of China[61573327];
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WOS记录号 | WOS:000662814700002
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Scopus记录号 | 2-s2.0-85134038702
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来源库 | Scopus
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引用统计 |
被引频次[WOS]:8
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成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/406625 |
专题 | 工学院_计算机科学与工程系 |
作者单位 | 1.School of Computer Science and Technology,University of Science and Technology of China,Hefei,Anhui,230027,China 2.School of Computer Science and Technology,Harbin Institute of Technology,Shenzhen,Guangdong,518055,China 3.School of Computer Science,Shaanxi Normal University,Xi’an,710119,China 4.Shenzhen Key Lab of Computational Intelligence,Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China |
推荐引用方式 GB/T 7714 |
Xu,Peilan,Luo,Wenjian,Lin,Xin,et al. BSO20: efficient brain storm optimization for real-parameter numerical optimization[J]. Complex & Intelligent Systems,2021,7(5):2415-2436.
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APA |
Xu,Peilan,Luo,Wenjian,Lin,Xin,Cheng,Shi,&Shi,Yuhui.(2021).BSO20: efficient brain storm optimization for real-parameter numerical optimization.Complex & Intelligent Systems,7(5),2415-2436.
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MLA |
Xu,Peilan,et al."BSO20: efficient brain storm optimization for real-parameter numerical optimization".Complex & Intelligent Systems 7.5(2021):2415-2436.
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条目包含的文件 | 条目无相关文件。 |
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