Cooperative multi-swarms Particle Swarm Optimizer for dynamic environment optimization

Guang Hui Wang; Jie Chen; Feng Pan

doi:10.1109/CHICC.2008.4605456

Cooperative multi-swarms Particle Swarm Optimizer for dynamic environment optimization

Guang Hui Wang^*, Jie Chen, Feng Pan

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

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

3 Citations (Scopus)

Abstract

Optimization problem in the dynamic environment is not only to locate a optimum, but track the moving optimum as close as possible. Particle Swarm Optimizer, a kind parallel random optimization method based on swarm intelligence, exhibits good performance for optimization problem. Particles converge at the local place quickly in basic Particle Swarm Optimizer(PSO), led to lose the ability to tracking the dynamic optima. To solve the problem, it's proposed the Cooperative Multi-Swarms Particle Swarm Optimizer(CmSPSO), which can cooperatively reinitialize a portion of particles in each swarm, which the distance between them is less than exclusive radius. Experiments have been made to demonstrate the simplicity and effectiveness, maintained the convergence and enhanced the diversity, and obtained the good effect at tracking the dynamic optima.

Original language	English
Title of host publication	Proceedings of the 27th Chinese Control Conference, CCC
Pages	43-48
Number of pages	6
DOIs	https://doi.org/10.1109/CHICC.2008.4605456
Publication status	Published - 2008
Event	27th Chinese Control Conference, CCC - Kunming, Yunnan, China Duration: 16 Jul 2008 → 18 Jul 2008

Publication series

Name	Proceedings of the 27th Chinese Control Conference, CCC

Conference

Conference	27th Chinese Control Conference, CCC
Country/Territory	China
City	Kunming, Yunnan
Period	16/07/08 → 18/07/08

Keywords

Average error ratio
Cooperative multi-swarms
Exclusive radius
Optimization in dynamic environment
Particle swarm optimizer (PSO)

Access to Document

10.1109/CHICC.2008.4605456

Cite this

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title = "Cooperative multi-swarms Particle Swarm Optimizer for dynamic environment optimization",

abstract = "Optimization problem in the dynamic environment is not only to locate a optimum, but track the moving optimum as close as possible. Particle Swarm Optimizer, a kind parallel random optimization method based on swarm intelligence, exhibits good performance for optimization problem. Particles converge at the local place quickly in basic Particle Swarm Optimizer(PSO), led to lose the ability to tracking the dynamic optima. To solve the problem, it's proposed the Cooperative Multi-Swarms Particle Swarm Optimizer(CmSPSO), which can cooperatively reinitialize a portion of particles in each swarm, which the distance between them is less than exclusive radius. Experiments have been made to demonstrate the simplicity and effectiveness, maintained the convergence and enhanced the diversity, and obtained the good effect at tracking the dynamic optima.",

keywords = "Average error ratio, Cooperative multi-swarms, Exclusive radius, Optimization in dynamic environment, Particle swarm optimizer (PSO)",

author = "Wang, {Guang Hui} and Jie Chen and Feng Pan",

year = "2008",

doi = "10.1109/CHICC.2008.4605456",

language = "English",

isbn = "9787900719706",

series = "Proceedings of the 27th Chinese Control Conference, CCC",

pages = "43--48",

booktitle = "Proceedings of the 27th Chinese Control Conference, CCC",

note = "27th Chinese Control Conference, CCC ; Conference date: 16-07-2008 Through 18-07-2008",

}

Wang, GH, Chen, J & Pan, F 2008, Cooperative multi-swarms Particle Swarm Optimizer for dynamic environment optimization. in Proceedings of the 27th Chinese Control Conference, CCC., 4605456, Proceedings of the 27th Chinese Control Conference, CCC, pp. 43-48, 27th Chinese Control Conference, CCC, Kunming, Yunnan, China, 16/07/08. https://doi.org/10.1109/CHICC.2008.4605456

Cooperative multi-swarms Particle Swarm Optimizer for dynamic environment optimization. / Wang, Guang Hui; Chen, Jie; Pan, Feng.
Proceedings of the 27th Chinese Control Conference, CCC. 2008. p. 43-48 4605456 (Proceedings of the 27th Chinese Control Conference, CCC).

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

TY - GEN

T1 - Cooperative multi-swarms Particle Swarm Optimizer for dynamic environment optimization

AU - Wang, Guang Hui

AU - Chen, Jie

AU - Pan, Feng

PY - 2008

Y1 - 2008

N2 - Optimization problem in the dynamic environment is not only to locate a optimum, but track the moving optimum as close as possible. Particle Swarm Optimizer, a kind parallel random optimization method based on swarm intelligence, exhibits good performance for optimization problem. Particles converge at the local place quickly in basic Particle Swarm Optimizer(PSO), led to lose the ability to tracking the dynamic optima. To solve the problem, it's proposed the Cooperative Multi-Swarms Particle Swarm Optimizer(CmSPSO), which can cooperatively reinitialize a portion of particles in each swarm, which the distance between them is less than exclusive radius. Experiments have been made to demonstrate the simplicity and effectiveness, maintained the convergence and enhanced the diversity, and obtained the good effect at tracking the dynamic optima.

AB - Optimization problem in the dynamic environment is not only to locate a optimum, but track the moving optimum as close as possible. Particle Swarm Optimizer, a kind parallel random optimization method based on swarm intelligence, exhibits good performance for optimization problem. Particles converge at the local place quickly in basic Particle Swarm Optimizer(PSO), led to lose the ability to tracking the dynamic optima. To solve the problem, it's proposed the Cooperative Multi-Swarms Particle Swarm Optimizer(CmSPSO), which can cooperatively reinitialize a portion of particles in each swarm, which the distance between them is less than exclusive radius. Experiments have been made to demonstrate the simplicity and effectiveness, maintained the convergence and enhanced the diversity, and obtained the good effect at tracking the dynamic optima.

KW - Average error ratio

KW - Cooperative multi-swarms

KW - Exclusive radius

KW - Optimization in dynamic environment

KW - Particle swarm optimizer (PSO)

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M3 - Conference contribution

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SN - 9787900719706

T3 - Proceedings of the 27th Chinese Control Conference, CCC

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BT - Proceedings of the 27th Chinese Control Conference, CCC

T2 - 27th Chinese Control Conference, CCC

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ER -

Cooperative multi-swarms Particle Swarm Optimizer for dynamic environment optimization

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Keywords

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