On the Analysis of Performance of the Artificial Searching Swarm Algorithm

Author

Chen, Tanggong ; Zhang, Lijie ; Liu, Zibin ; Pang, Lingling ; Shu, Qunfang

Author_Institution

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

Volume

4

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

365

Lastpage

368

Abstract

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

Keywords

genetic algorithms; particle swarm optimisation; search problems; ASSA performance evaluation; artificial fish-swarm algorithm; artificial searching swarm algorithm; bionic intelligent optimization algorithm simulation; genetic algorithm; optimization multivariable function; particle swarm optimization; Algorithm design and analysis; Ant colony optimization; Artificial intelligence; Biological system modeling; Computational biology; Design optimization; Genetic algorithms; Optimization methods; Particle swarm optimization; Performance analysis; artificial searching swarm algorithm; bionic intelligent optimization algorithm; genetic algorithm; optimization; particle swarm algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.162

Filename

5366986