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Evolutionary method combining particle swarm optimization and genetic algorithms using fuzzy logic for decision making

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3 Author(s)
Fevrier Valdez ; The Department of Computer Science, Tijuana ; Patricia Melin ; Oscar Castillo

We describe in this paper a new hybrid approach for mathematical function optimization combining Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) using Fuzzy Logic to integrate the results. The new evolutionary method combines the advantages of PSO and GA to give us an improved PSO+GA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible. The new hybrid PSO+GA approach is compared with the PSO and GA methods with a set of benchmark mathematical functions. The new hybrid PSO+GA method is shown to be superior that the individual evolutionary methods. The mathematical functions were evaluated with 2, 4, 8 and 32 variables to validate this approach.

Published in:

Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on

Date of Conference:

20-24 Aug. 2009