A new hybrid differential evolution with wavelet based mutation and crossover

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

A new hybrid differential evolution with wavelet based mutation and crossover

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

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

2 Citations (Scopus)

Abstract

An improved Differential Evolution (DE) that incorporates wavelet-based mutation and crossover operations is proposed. In the mutation operation, the scaling factor is controlled by a wavelet function. In the crossover operation, the trial population vectors are modified by a wavelet function. The wavelet theory applied is to enhance DE in exploring the solution space more effectively for a better solution. A suite of benchmarktest functions is employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the conventional 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	722-729
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	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{9d7e24af38a949658f15924c121fb34f,

title = "A new hybrid differential evolution with wavelet based mutation and crossover",

abstract = "An improved Differential Evolution (DE) that incorporates wavelet-based mutation and crossover operations is proposed. In the mutation operation, the scaling factor is controlled by a wavelet function. In the crossover operation, the trial population vectors are modified by a wavelet function. The wavelet theory applied is to enhance DE in exploring the solution space more effectively for a better solution. A suite of benchmarktest functions is employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the conventional methods in terms of convergence speed, solution quality and solution stability.",

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

year = "2009",

month = dec,

day = "1",

language = "English",

pages = "722--729",

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",

}

Lai, JCY, Yeung, CW & Leung, HFF 2009, A new hybrid differential evolution with wavelet based mutation and crossover. in APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. pp. 722-729, Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009, Sapporo, Japan, 4/10/09.

A new hybrid differential evolution with wavelet based mutation and crossover. / Lai, J. C.Y.; Yeung, C. W.; Leung, Hung Fat Frank.

APSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference. 2009. p. 722-729.

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

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AU - Yeung, C. W.

AU - Leung, Hung Fat Frank

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N2 - An improved Differential Evolution (DE) that incorporates wavelet-based mutation and crossover operations is proposed. In the mutation operation, the scaling factor is controlled by a wavelet function. In the crossover operation, the trial population vectors are modified by a wavelet function. The wavelet theory applied is to enhance DE in exploring the solution space more effectively for a better solution. A suite of benchmarktest functions is employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the conventional methods in terms of convergence speed, solution quality and solution stability.

AB - An improved Differential Evolution (DE) that incorporates wavelet-based mutation and crossover operations is proposed. In the mutation operation, the scaling factor is controlled by a wavelet function. In the crossover operation, the trial population vectors are modified by a wavelet function. The wavelet theory applied is to enhance DE in exploring the solution space more effectively for a better solution. A suite of benchmarktest functions is employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the conventional methods in terms of convergence speed, solution quality and solution stability.

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M3 - Conference article published in proceeding or book

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Y2 - 4 October 2009 through 7 October 2009

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