A Novel Binary Particle Swarm Optimization Method Using Artificial Immune System

Author

Afshinmanesh, Farzaneh ; Marandi, Alireza ; Rahimi-Kian, Ashkan

Author_Institution

Sch. of ECE, Tehran Univ.

Volume

1

fYear

2005

fDate

21-24 Nov. 2005

Firstpage

217

Lastpage

220

Abstract

Particle swarm optimization, a nature-inspired evolutionary algorithm, has been successful in solving a wide range of real value optimization problems. However, little attempts have been made to extend it to discrete problems. In this paper, a new binary particle swarm optimization method based on the theory of immunity in biology is proposed. In spite of the simplicity of the technique, simulation results show the improvement of the searching ability and increment in the convergence speed in comparison with the other binary PSO and genetic algorithm

Keywords

particle swarm optimisation; artificial immune system; binary particle swarm optimization; convergence speed; discrete particle swarm optimization; evolutionary algorithm; genetic algorithm; immunity theory; real value optimization; searching ability; Artificial immune systems; Biological system modeling; Competitive intelligence; Convergence; Evolutionary computation; Genetic algorithms; Immune system; Optimization methods; Particle swarm optimization; Power system modeling; Artificial Immune System; Discrete Particle Swarm Optimization; Negative Selection;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer as a Tool, 2005. EUROCON 2005.The International Conference on

Conference_Location

Belgrade

Print_ISBN

1-4244-0049-X

Type

conf

DOI

10.1109/EURCON.2005.1629899

Filename

1629899