On the Analysis of Performance of the Improved Artificial Searching Swarm Algorithm

Author

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

Author_Institution

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

fYear

2009

fDate

1-3 Nov. 2009

Firstpage

502

Lastpage

506

Abstract

Artificial searching swarm algorithm (ASSA) is a new optimization algorithm. This paper presents two type behaviors rules of searching swarm, and discusses the performance of the algorithm based on the different rules. By analyzing the simulation results, an improved ASSA with mutative searching step is proposed. The function simulation tests prove that the improved algorithm implements better performance than that of original algorithm in both searching precision and convergent speed.

Keywords

artificial intelligence; search problems; artificial searching swarm algorithm; function simulation test; mutative searching step; optimization algorithm; Algorithm design and analysis; Analytical models; Ant colony optimization; Artificial intelligence; Biological system modeling; Design optimization; Genetic algorithms; Intelligent networks; Particle swarm optimization; Performance analysis; artificial searching swarm algorithm; bionic intelligent optimization algorithm; evolutionary computation; optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-5557-7

Electronic_ISBN

978-0-7695-3852-5

Type

conf

DOI

10.1109/ICINIS.2009.134

Filename

5363388