Chaotic cooperative particle swarm optimization based on tent map

Xin Jing; Xiujie Zhang; Shenmin Song

doi:10.1109/ICIECS.2009.5365043

Chaotic cooperative particle swarm optimization based on tent map

Xin Jing^*
, Xiujie Zhang
, Shenmin Song

^*Corresponding author for this work

School of Astronautics

Harbin Institute of Technology

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

3 Scopus citations

Abstract

In this paper, a chaotic cooperative particle swarm optimization based on Tent map (TCCPSO) is proposed. The cooperative particle swarm optimization (CPSO), can significantly improve the performance of the original algorithm. However, CPSO has the defect of leading to pseudominimizer, which can not be easily escaped by interleaving the CPSO and PSO algorithm. Therefore, we take full advantages of the characteristics of ergodicity and randomness of chaotic variables to help the particles escape from pseudominimizer and converge to global optimum. The experimental results on some benchmark functions show that TCCPSO outperforms the CPSO. In addition, simulation results show that algorithm computation precision is increased and that the algorithm convergence is improved.

Original language	English
Title of host publication	Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009
DOIs	https://doi.org/10.1109/ICIECS.2009.5365043
State	Published - 2009
Event	2009 International Conference on Information Engineering and Computer Science, ICIECS 2009 - Wuhan, China Duration: 19 Dec 2009 → 20 Dec 2009

Publication series

Name	Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

Conference

Conference	2009 International Conference on Information Engineering and Computer Science, ICIECS 2009
Country/Territory	China
City	Wuhan
Period	19/12/09 → 20/12/09

Keywords

Chaotic mutation
Cooperative particle swarm optimization
Particle swarm optimization

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10.1109/ICIECS.2009.5365043

Cite this

Jing, X., Zhang, X., & Song, S. (2009). Chaotic cooperative particle swarm optimization based on tent map. In Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009 Article 5365043 (Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009). https://doi.org/10.1109/ICIECS.2009.5365043

@inproceedings{95941c5ae8df4c6d9c92a305a9b13f2b,

title = "Chaotic cooperative particle swarm optimization based on tent map",

abstract = "In this paper, a chaotic cooperative particle swarm optimization based on Tent map (TCCPSO) is proposed. The cooperative particle swarm optimization (CPSO), can significantly improve the performance of the original algorithm. However, CPSO has the defect of leading to pseudominimizer, which can not be easily escaped by interleaving the CPSO and PSO algorithm. Therefore, we take full advantages of the characteristics of ergodicity and randomness of chaotic variables to help the particles escape from pseudominimizer and converge to global optimum. The experimental results on some benchmark functions show that TCCPSO outperforms the CPSO. In addition, simulation results show that algorithm computation precision is increased and that the algorithm convergence is improved.",

keywords = "Chaotic mutation, Cooperative particle swarm optimization, Particle swarm optimization",

author = "Xin Jing and Xiujie Zhang and Shenmin Song",

year = "2009",

doi = "10.1109/ICIECS.2009.5365043",

language = "英语",

isbn = "9781424449941",

series = "Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009",

booktitle = "Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009",

note = "2009 International Conference on Information Engineering and Computer Science, ICIECS 2009 ; Conference date: 19-12-2009 Through 20-12-2009",

}

Jing, X, Zhang, X & Song, S 2009, Chaotic cooperative particle swarm optimization based on tent map. in Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009., 5365043, Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009, 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009, Wuhan, China, 19/12/09. https://doi.org/10.1109/ICIECS.2009.5365043

Chaotic cooperative particle swarm optimization based on tent map. / Jing, Xin; Zhang, Xiujie; Song, Shenmin.
Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009. 2009. 5365043 (Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009).

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

TY - GEN

T1 - Chaotic cooperative particle swarm optimization based on tent map

AU - Jing, Xin

AU - Zhang, Xiujie

AU - Song, Shenmin

PY - 2009

Y1 - 2009

N2 - In this paper, a chaotic cooperative particle swarm optimization based on Tent map (TCCPSO) is proposed. The cooperative particle swarm optimization (CPSO), can significantly improve the performance of the original algorithm. However, CPSO has the defect of leading to pseudominimizer, which can not be easily escaped by interleaving the CPSO and PSO algorithm. Therefore, we take full advantages of the characteristics of ergodicity and randomness of chaotic variables to help the particles escape from pseudominimizer and converge to global optimum. The experimental results on some benchmark functions show that TCCPSO outperforms the CPSO. In addition, simulation results show that algorithm computation precision is increased and that the algorithm convergence is improved.

AB - In this paper, a chaotic cooperative particle swarm optimization based on Tent map (TCCPSO) is proposed. The cooperative particle swarm optimization (CPSO), can significantly improve the performance of the original algorithm. However, CPSO has the defect of leading to pseudominimizer, which can not be easily escaped by interleaving the CPSO and PSO algorithm. Therefore, we take full advantages of the characteristics of ergodicity and randomness of chaotic variables to help the particles escape from pseudominimizer and converge to global optimum. The experimental results on some benchmark functions show that TCCPSO outperforms the CPSO. In addition, simulation results show that algorithm computation precision is increased and that the algorithm convergence is improved.

KW - Chaotic mutation

KW - Cooperative particle swarm optimization

KW - Particle swarm optimization

UR - https://www.scopus.com/pages/publications/77949601363

U2 - 10.1109/ICIECS.2009.5365043

DO - 10.1109/ICIECS.2009.5365043

M3 - 会议稿件

AN - SCOPUS:77949601363

SN - 9781424449941

T3 - Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

BT - Proceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

T2 - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

Y2 - 19 December 2009 through 20 December 2009

ER -

Chaotic cooperative particle swarm optimization based on tent map

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