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

^*Corresponding author for this work

School of Medical and Technology

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

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.

Original language	English
Title of host publication	International Conference on Intelligent Computing, ICIC 2006, Proceedings
Publisher	Springer Verlag
Pages	964-974
Number of pages	11
ISBN (Print)	3540372717, 9783540372714
DOIs	https://doi.org/10.1007/11816157_117
Publication status	Published - 2006
Event	International Conference on Intelligent Computing, ICIC 2006 - Kunming, China Duration: 16 Aug 2006 → 19 Aug 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4113 LNCS - I
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Intelligent Computing, ICIC 2006
Country/Territory	China
City	Kunming
Period	16/08/06 → 19/08/06

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10.1007/11816157_117

Cite this

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

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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",

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

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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",

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Wang, L, Liu, Y & Xu, Y 2006, Multi-objective PSO algorithm based on fitness sharing and online elite archiving. in 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), vol. 4113 LNCS - I, Springer Verlag, pp. 964-974, International Conference on Intelligent Computing, ICIC 2006, Kunming, China, 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. p. 964-974 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4113 LNCS - I).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Liu, Yushu

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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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Wang L, Liu Y, Xu Y. Multi-objective PSO algorithm based on fitness sharing and online elite archiving. In International Conference on Intelligent Computing, ICIC 2006, Proceedings. Springer Verlag. 2006. p. 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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