Multi-objective PSO algorithm based on fitness sharing and online elite archiving

Li Wang; Yushu Liu; Yuanqing Xu

doi:10.1007/11816157_117

Multi-objective PSO algorithm based on fitness sharing and online elite archiving

Li Wang^*, Yushu Liu, Yuanqing Xu

^*此作品的通讯作者

医学技术学院

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

5 引用（Scopus）

摘要

A new technique for multi-objective PSO (Particle Swarm Optimization) based on fitness sharing and online elite archiving is proposed. Global best position of particle swarm is selected from repository by fitness sharing, which guarantees the diversity of the population. At the same time, in order to ensure the excellent population, the elite particles from the repository are introduced into next iteration. Three well-known test functions taken from the multi-objective optimization literature are used to evaluate the performance of the proposed approach. The results indicate that our approach generates a satisfactory approximation of the Pareto front and spread widely along the front.

源语言	英语
主期刊名	International Conference on Intelligent Computing, ICIC 2006, Proceedings
出版商	Springer Verlag
页	964-974
页数	11
ISBN（印刷版）	3540372717, 9783540372714
DOI	https://doi.org/10.1007/11816157_117
出版状态	已出版 - 2006
活动	International Conference on Intelligent Computing, ICIC 2006 - Kunming, 中国期限: 16 8月 2006 → 19 8月 2006

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	4113 LNCS - I
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	International Conference on Intelligent Computing, ICIC 2006
国家/地区	中国
市	Kunming
时期	16/08/06 → 19/08/06

访问文件

10.1007/11816157_117

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引用此

Wang, L., Liu, Y., & Xu, Y. (2006). Multi-objective PSO algorithm based on fitness sharing and online elite archiving. 在 International Conference on Intelligent Computing, ICIC 2006, Proceedings (页码 964-974). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 4113 LNCS - I). Springer Verlag. https://doi.org/10.1007/11816157_117

Wang, Li ; Liu, Yushu ; Xu, Yuanqing. / Multi-objective PSO algorithm based on fitness sharing and online elite archiving. International Conference on Intelligent Computing, ICIC 2006, Proceedings. Springer Verlag, 2006. 页码 964-974 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{6b4af0a69edb4aea82378b1f28b36fae,

title = "Multi-objective PSO algorithm based on fitness sharing and online elite archiving",

abstract = "A new technique for multi-objective PSO (Particle Swarm Optimization) based on fitness sharing and online elite archiving is proposed. Global best position of particle swarm is selected from repository by fitness sharing, which guarantees the diversity of the population. At the same time, in order to ensure the excellent population, the elite particles from the repository are introduced into next iteration. Three well-known test functions taken from the multi-objective optimization literature are used to evaluate the performance of the proposed approach. The results indicate that our approach generates a satisfactory approximation of the Pareto front and spread widely along the front.",

author = "Li Wang and Yushu Liu and Yuanqing Xu",

year = "2006",

doi = "10.1007/11816157_117",

language = "English",

isbn = "3540372717",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "964--974",

booktitle = "International Conference on Intelligent Computing, ICIC 2006, Proceedings",

address = "Germany",

note = "International Conference on Intelligent Computing, ICIC 2006 ; Conference date: 16-08-2006 Through 19-08-2006",

}

Wang, L, Liu, Y & Xu, Y 2006, Multi-objective PSO algorithm based on fitness sharing and online elite archiving. 在 International Conference on Intelligent Computing, ICIC 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 4113 LNCS - I, Springer Verlag, 页码 964-974, International Conference on Intelligent Computing, ICIC 2006, Kunming, 中国, 16/08/06. https://doi.org/10.1007/11816157_117

Multi-objective PSO algorithm based on fitness sharing and online elite archiving. / Wang, Li; Liu, Yushu; Xu, Yuanqing.
International Conference on Intelligent Computing, ICIC 2006, Proceedings. Springer Verlag, 2006. 页码 964-974 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 4113 LNCS - I).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

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AU - Liu, Yushu

AU - Xu, Yuanqing

PY - 2006

Y1 - 2006

N2 - A new technique for multi-objective PSO (Particle Swarm Optimization) based on fitness sharing and online elite archiving is proposed. Global best position of particle swarm is selected from repository by fitness sharing, which guarantees the diversity of the population. At the same time, in order to ensure the excellent population, the elite particles from the repository are introduced into next iteration. Three well-known test functions taken from the multi-objective optimization literature are used to evaluate the performance of the proposed approach. The results indicate that our approach generates a satisfactory approximation of the Pareto front and spread widely along the front.

AB - A new technique for multi-objective PSO (Particle Swarm Optimization) based on fitness sharing and online elite archiving is proposed. Global best position of particle swarm is selected from repository by fitness sharing, which guarantees the diversity of the population. At the same time, in order to ensure the excellent population, the elite particles from the repository are introduced into next iteration. Three well-known test functions taken from the multi-objective optimization literature are used to evaluate the performance of the proposed approach. The results indicate that our approach generates a satisfactory approximation of the Pareto front and spread widely along the front.

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U2 - 10.1007/11816157_117

DO - 10.1007/11816157_117

M3 - Conference contribution

AN - SCOPUS:33749543902

SN - 3540372717

SN - 9783540372714

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - International Conference on Intelligent Computing, ICIC 2006, Proceedings

PB - Springer Verlag

T2 - International Conference on Intelligent Computing, ICIC 2006

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ER -

Wang L, Liu Y, Xu Y. Multi-objective PSO algorithm based on fitness sharing and online elite archiving. 在 International Conference on Intelligent Computing, ICIC 2006, Proceedings. Springer Verlag. 2006. 页码 964-974. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11816157_117

Multi-objective PSO algorithm based on fitness sharing and online elite archiving

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