A novel Fuzzy Particle Swarm Optimization

Author

Aminian, Ehsan ; Teshnehlab, Mohammad

Author_Institution

Dept. of Comput. Eng., Islamic Azad Univ., Tehran, Iran

fYear

2013

fDate

27-29 Aug. 2013

Firstpage

1

Lastpage

6

Abstract

In this paper, we introduce a novel Fuzzy particle Swarm Optimization method in which the inertia weight as well as the cognitive and social coefficients are adjusted for each particle separately according to the information coming from a Fuzzy Logic Controller. We illustrate the efficiency of our method in comparison with the origin version of inertia Weight Particle Swarm Optimization. Although the curse of dimensionality has always been one of significant weaknesses in Evolutionary Algorithms, we show it has the least influence on the proposed method compared to PSO and original WPSO. We also prove that our method outperforms other Fuzzy-PSO versions by testing two benchmark functions.

Keywords

fuzzy control; particle swarm optimisation; benchmark functions; dimensionality curse; evolutionary algorithms; fuzzy PSO versions; fuzzy logic controller; fuzzy particle swarm optimization; inertia weight particle swarm optimization; particles level; social coefficients; Adaptive Particle swarm optimization; Evolutionary computation; Fuzzy Logic Controller and Social model;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (IFSC), 2013 13th Iranian Conference on

Conference_Location

Qazvin

Print_ISBN

978-1-4799-1227-8

Type

conf

DOI

10.1109/IFSC.2013.6675618

Filename

6675618