Intelligent fuzzy particle swarm optimization with cross-mutated operation

Publisher:
IEEE
Publication Type:
Conference Proceeding
Citation:
IEEE Congress on Evolutionary Computation, 2012, pp. 3009 - 3016
Issue Date:
2012-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2012001707OK.pdf939.07 kB
Adobe PDF
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
Please use this identifier to cite or link to this item: