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 proceedingConference article published in proceeding or bookAcademic researchpeer-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 languageEnglish
Title of host publicationAPSIPA ASC 2009 - Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference
Pages730-737
Number of pages8
Publication statusPublished - 1 Dec 2009
EventAsia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 - Sapporo, Japan
Duration: 4 Oct 20097 Oct 2009

Conference

ConferenceAsia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009
CountryJapan
CitySapporo
Period4/10/097/10/09

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering
  • Communication

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