Cooperative particle swarm optimizer with elimination mechanism for global optimization of multimodal problems

Geng Zhang; Yangmin Li

doi:10.1109/CEC.2014.6900267

Cooperative particle swarm optimizer with elimination mechanism for global optimization of multimodal problems

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

9 Citations (Scopus)

Abstract

This paper presents a new particle swarm optimizer (PSO) that called the cooperative particle swarm optimizer with elimination mechanism (CPSO-EM) in an attempt to address the issue of getting trapped into local optimum when solving nonseparable multimodal problems using PSO algorithm. The proposed CPSO-EM builds on the basis of an early cooperative PSO (CPSO-H) that employs cooperative behavior. The CPSO-H and elimination mechanism (EM) memory are incorporated together to obtain CPSO-EM. Experimental studies on a set of test functions show that CPSO-EM exhibits better performance in solving nonseparable multimodal problems than several other peer algorithms.

Original language	English
Title of host publication	Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
Publisher	IEEE
Pages	210-217
Number of pages	8
ISBN (Electronic)	9781479914883
DOIs	https://doi.org/10.1109/CEC.2014.6900267
Publication status	Published - 1 Jan 2014
Externally published	Yes
Event	2014 IEEE Congress on Evolutionary Computation, CEC 2014 - Beijing, China Duration: 6 Jul 2014 → 11 Jul 2014

Conference

Conference	2014 IEEE Congress on Evolutionary Computation, CEC 2014
Country/Territory	China
City	Beijing
Period	6/07/14 → 11/07/14

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics
Theoretical Computer Science

More information

10.1109/CEC.2014.6900267

Cite this

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title = "Cooperative particle swarm optimizer with elimination mechanism for global optimization of multimodal problems",

abstract = "This paper presents a new particle swarm optimizer (PSO) that called the cooperative particle swarm optimizer with elimination mechanism (CPSO-EM) in an attempt to address the issue of getting trapped into local optimum when solving nonseparable multimodal problems using PSO algorithm. The proposed CPSO-EM builds on the basis of an early cooperative PSO (CPSO-H) that employs cooperative behavior. The CPSO-H and elimination mechanism (EM) memory are incorporated together to obtain CPSO-EM. Experimental studies on a set of test functions show that CPSO-EM exhibits better performance in solving nonseparable multimodal problems than several other peer algorithms.",

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Cooperative particle swarm optimizer with elimination mechanism for global optimization of multimodal problems. / Zhang, Geng; Li, Yangmin.
Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. IEEE, 2014. p. 210-217 6900267.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - This paper presents a new particle swarm optimizer (PSO) that called the cooperative particle swarm optimizer with elimination mechanism (CPSO-EM) in an attempt to address the issue of getting trapped into local optimum when solving nonseparable multimodal problems using PSO algorithm. The proposed CPSO-EM builds on the basis of an early cooperative PSO (CPSO-H) that employs cooperative behavior. The CPSO-H and elimination mechanism (EM) memory are incorporated together to obtain CPSO-EM. Experimental studies on a set of test functions show that CPSO-EM exhibits better performance in solving nonseparable multimodal problems than several other peer algorithms.

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Cooperative particle swarm optimizer with elimination mechanism for global optimization of multimodal problems

Abstract

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ASJC Scopus subject areas

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