Intelligent fuzzy particle swarm optimization with cross-mutated operation

Sai Ho Ling, Hung T. Nguyen, Hung Fat Frank Leung, Kit Yan Chan, Frank Jiang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)

Abstract

This paper presents a novel fuzzy particle swarm optimization with cross-mutated operation (FPSOCM), where a fuzzy logic is applied to determine the inertia weight of PSO and the control parameter of the proposed cross-mutated operation based on human knowledge. By introducing the fuzzy system, the value of the inertia weight of PSO becomes adaptive. The new cross-mutated operation effectively drives the solution to escape from local optima. To illustrate the performance of the FPSOCM, a suite of benchmark test functions are employed. Experimental results show the proposed FPSOCMmethod performs better than some existing hybrid PSO methods in terms of solution quality and solution reliability (standard deviation upon many trials). Moreover, an industrial application of economic load dispatch is given to show that the FPSOCM method performs statistically more significant than the existing hybrid PSO methods.
Original languageEnglish
Title of host publication2012 IEEE Congress on Evolutionary Computation, CEC 2012
DOIs
Publication statusPublished - 4 Oct 2012
Event2012 IEEE Congress on Evolutionary Computation, CEC 2012 - Brisbane, QLD, Australia
Duration: 10 Jun 201215 Jun 2012

Conference

Conference2012 IEEE Congress on Evolutionary Computation, CEC 2012
CountryAustralia
CityBrisbane, QLD
Period10/06/1215/06/12

Keywords

  • Cross-mutated operation
  • Economic load dispatch
  • Fuzzy logic
  • Inertia weight
  • Particle swarm optimization

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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