Fuzzy Quantum-Behaved Particle Swarm Optimization Algorithm

Author

Zhao, Wei ; San, Ye ; Shi, Huishu

Author_Institution

Control & Simulation Center, Harbin Inst. of Technol., Harbin, China

Volume

1

fYear

2010

fDate

29-31 Oct. 2010

Firstpage

49

Lastpage

52

Abstract

Aiming at the drawback of being easily trapped into the local optima and premature convergence in quantum-behaved particle swarm optimization algorithm, fuzzy quantum-behaved particle swarm optimization algorithm was proposed. In fuzzy quantum-behaved particle swarm optimization algorithm, the center of potential of particle was influenced by more than two particles in the neighborhood and the influence was defined as fuzzy variable that is computed by Gaussian distribution. The simulation results of testing four standard benchmark functions demonstrate that fuzzy quantum-behaved particle swarm optimization algorithm has best optimization performance and robustness, the validity and feasibility of the method are verified.

Keywords

Gaussian distribution; fuzzy set theory; particle swarm optimisation; quantum theory; Gaussian distribution; convergence; fuzzy quantum behaved particle swarm optimization; fuzzy variable; Algorithm design and analysis; Benchmark testing; Convergence; IEEE Press; Optimization; Particle swarm optimization; Robustness; Gaussian distribution; fuzzy variable; quantum-behaved particle swarm optimization algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design (ISCID), 2010 International Symposium on

Conference_Location

Hangzhou

Print_ISBN

978-1-4244-8094-4

Type

conf

DOI

10.1109/ISCID.2010.20

Filename

5692660