Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation

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...

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Main Authors: Ling, S., Nguye, H., Leung, F., Chan, Kit Yan, Jiang, F.
Other Authors: IEEE
Format: Conference Paper
Published: IEEE 2012
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/35908
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author Ling, S.
Nguye, H.
Leung, F.
Chan, Kit Yan
Jiang, F.
author2 IEEE
author_facet IEEE
Ling, S.
Nguye, H.
Leung, F.
Chan, Kit Yan
Jiang, F.
author_sort Ling, S.
building Curtin Institutional Repository
collection Online Access
description 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 FPSOCM method 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.
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institution Curtin University Malaysia
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publishDate 2012
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spelling curtin-20.500.11937-359082018-03-29T09:08:51Z Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation Ling, S. Nguye, H. Leung, F. Chan, Kit Yan Jiang, F. IEEE Fuzzy logic Inertia weight Cross-mutated operation Particle swarm optimization Economic load dispatch 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 FPSOCM method 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. 2012 Conference Paper http://hdl.handle.net/20.500.11937/35908 10.1109/CEC.2012.6252934 IEEE restricted
spellingShingle Fuzzy logic
Inertia weight
Cross-mutated operation
Particle swarm optimization
Economic load dispatch
Ling, S.
Nguye, H.
Leung, F.
Chan, Kit Yan
Jiang, F.
Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation
title Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation
title_full Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation
title_fullStr Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation
title_full_unstemmed Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation
title_short Intelligent Fuzzy Particle Swarm Optimization with Cross-Mutated Operation
title_sort intelligent fuzzy particle swarm optimization with cross-mutated operation
topic Fuzzy logic
Inertia weight
Cross-mutated operation
Particle swarm optimization
Economic load dispatch
url http://hdl.handle.net/20.500.11937/35908