A particle swarm optimization with multi-mutation operation based on wavelet theory

C. W. Yeung; J. C.Y. Lai; Hung Fat Frank Leung

A particle swarm optimization with multi-mutation operation based on wavelet theory

C. W. Yeung, J. C.Y. Lai, Hung Fat Frank Leung

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

1 Citation (Scopus)

Abstract

An improved hybrid particle swarm optimization (PSO) that incorporates a wavelet-based multi-mutation operation is proposed. It applies wavelet theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.

Original language	English
Title of host publication	APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference
Pages	730-737
Number of pages	8
Publication status	Published - 1 Dec 2009
Event	Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 - Sapporo, Japan Duration: 4 Oct 2009 → 7 Oct 2009

Conference

Conference	Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009
Country/Territory	Japan
City	Sapporo
Period	4/10/09 → 7/10/09

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Electrical and Electronic Engineering
Communication

Cite this

@inproceedings{64a5d58dddc64658aa5c57fe9409b714,

title = "A particle swarm optimization with multi-mutation operation based on wavelet theory",

abstract = "An improved hybrid particle swarm optimization (PSO) that incorporates a wavelet-based multi-mutation operation is proposed. It applies wavelet theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.",

author = "Yeung, {C. W.} and Lai, {J. C.Y.} and Leung, {Hung Fat Frank}",

year = "2009",

month = dec,

day = "1",

language = "English",

pages = "730--737",

booktitle = "APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference",

note = "Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 ; Conference date: 04-10-2009 Through 07-10-2009",

}

Yeung, CW, Lai, JCY & Leung, HFF 2009, A particle swarm optimization with multi-mutation operation based on wavelet theory. in APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. pp. 730-737, Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009, Sapporo, Japan, 4/10/09.

A particle swarm optimization with multi-mutation operation based on wavelet theory. / Yeung, C. W.; Lai, J. C.Y.; Leung, Hung Fat Frank.

APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. 2009. p. 730-737.

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

TY - GEN

T1 - A particle swarm optimization with multi-mutation operation based on wavelet theory

AU - Yeung, C. W.

AU - Lai, J. C.Y.

AU - Leung, Hung Fat Frank

PY - 2009/12/1

Y1 - 2009/12/1

N2 - An improved hybrid particle swarm optimization (PSO) that incorporates a wavelet-based multi-mutation operation is proposed. It applies wavelet theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.

AB - An improved hybrid particle swarm optimization (PSO) that incorporates a wavelet-based multi-mutation operation is proposed. It applies wavelet theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.

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M3 - Conference article published in proceeding or book

SP - 730

EP - 737

BT - APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference

T2 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009

Y2 - 4 October 2009 through 7 October 2009

ER -

A particle swarm optimization with multi-mutation operation based on wavelet theory

Abstract

Conference

ASJC Scopus subject areas

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