On the Analysis of Performance of the Artificial Tribe Algorithm

Author

Chen, Tanggong ; Wei, Xiaowei ; Jia, Wenhui ; Liu, Zhi

Author_Institution

Province-Minist. Joint Key Lab. of Electromagn. Field & Electr. Apparatus Reliability, Hebei Univ. of Technol., Tianjin, China

Volume

1

fYear

2010

fDate

28-31 May 2010

Firstpage

60

Lastpage

63

Abstract

Artificial Tribe Algorithm (ATA) is a novel intelligent optimization algorithm based on the simulation of bionic intelligent optimization algorithm. This work discusses the main factors which influence the performance of ATA, and compares the performance of ATA with that of genetic algorithm (GA), particle swarm optimization (PSO), and artificial fish-swarm algorithm (AFSA) for optimization multivariable functions. The simulation results showed that ATA outperforms the mentioned algorithms in global optimization problems.

Keywords

genetic algorithms; particle swarm optimisation; artificial fish-swarm algorithm; artificial tribe algorithm; bionic intelligent optimization algorithm; genetic algorithm; optimization multivariable functions; particle swarm optimization; performance analysis; Algorithm design and analysis; Ant colony optimization; Artificial intelligence; Design optimization; Electromagnetic analysis; Electromagnetic fields; Genetic algorithms; Optimization methods; Particle swarm optimization; Performance analysis; artificial fish-swarm algorithm; artificial tribe algorithm; bionic intelligent optimization algorithm; genetic algorithm; optimization; particle swarm algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Optimization (CSO), 2010 Third International Joint Conference on

Conference_Location

Huangshan, Anhui

Print_ISBN

978-1-4244-6812-6

Electronic_ISBN

978-1-4244-6813-3

Type

conf

DOI

10.1109/CSO.2010.112

Filename

5533148