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Parallel particle swarm optimization with parameters adaptation using fuzzy logic

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2013) 7630 LNAI(PART 2) 374-385
DOI: 10.1007/978-3-642-37798-3_33
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Abstract

We describe in this paper a Parallel Particle Swarm Optimization (PPSO) method with dynamic parameter adaptation to optimize complex mathematical functions. Fuzzy Logic is used to adapt the parameters of the PSO in the best way possible. The PPSO is shown to be superior to the individual evolutionary methods on the set of benchmark functions. © 2013 Springer-Verlag.

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Valdez, F., Melin, P., & Castillo, O. (2013). Parallel particle swarm optimization with parameters adaptation using fuzzy logic. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7630 LNAI, pp. 374–385). https://doi.org/10.1007/978-3-642-37798-3_33

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