Intelligent fuzzy particle swarm optimization with cross-mutated operation

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

doi:10.1109/CEC.2012.6252934

Intelligent fuzzy particle swarm optimization with cross-mutated operation

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

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-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 language	English
Title of host publication	2012 IEEE Congress on Evolutionary Computation, CEC 2012
DOIs	https://doi.org/10.1109/CEC.2012.6252934
Publication status	Published - 4 Oct 2012
Event	2012 IEEE Congress on Evolutionary Computation, CEC 2012 - Brisbane, QLD, Australia Duration: 10 Jun 2012 → 15 Jun 2012

Conference

Conference	2012 IEEE Congress on Evolutionary Computation, CEC 2012
Country/Territory	Australia
City	Brisbane, QLD
Period	10/06/12 → 15/06/12

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

More information

10.1109/CEC.2012.6252934

Cite this

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title = "Intelligent fuzzy particle swarm optimization with cross-mutated operation",

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.",

keywords = "Cross-mutated operation, Economic load dispatch, Fuzzy logic, Inertia weight, Particle swarm optimization",

author = "Ling, {Sai Ho} and Nguyen, {Hung T.} and Leung, {Hung Fat Frank} and Chan, {Kit Yan} and Frank Jiang",

year = "2012",

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AU - Ling, Sai Ho

AU - Nguyen, Hung T.

AU - Leung, Hung Fat Frank

AU - Chan, Kit Yan

AU - Jiang, Frank

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AB - 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.

KW - Cross-mutated operation

KW - Economic load dispatch

KW - Fuzzy logic

KW - Inertia weight

KW - Particle swarm optimization

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DO - 10.1109/CEC.2012.6252934

M3 - Conference article published in proceeding or book

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BT - 2012 IEEE Congress on Evolutionary Computation, CEC 2012

T2 - 2012 IEEE Congress on Evolutionary Computation, CEC 2012

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Intelligent fuzzy particle swarm optimization with cross-mutated operation

Abstract

Conference

Keywords

ASJC Scopus subject areas

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