Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17205
Title: Intelligent fuzzy particle swarm optimization with cross-mutated operation
Authors: Ling, SH
Nguyen, HT
Leung, FHF 
Chan, KY
Jiang, F
Issue Date: 2012
Source: 2012 IEEE Congress on Evolutionary Computation (CEC), 10-15 June 2012, Brisbane, QLD, p. 1-8
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 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.
Keywords: Cross-mutated operation
Economic load dispatch
Fuzzy logic
Inertia weight
Particle swarm optimization
Publisher: IEEE
ISBN: 978-1-4673-1510-4
978-1-4673-1508-1 (E-ISBN)
DOI: 10.1109/CEC.2012.6252934
Appears in Collections:Conference Paper

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