Artificial Searching Swarm Algorithm for solving constrained optimization problems

Author

Chen, Tanggong ; Pang, Lingling ; Du, Jiang ; Liu, Zibin ; Zhang, Lijie

Author_Institution

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

Volume

1

fYear

2009

fDate

20-22 Nov. 2009

Firstpage

562

Lastpage

565

Abstract

Artificial searching swarm algorithm (ASSA) is a novel optimization algorithm. This paper presents the comparison results on the performance of the ASSA for solving constrained optimization problems. The penalty function method and non-parameter penalty method are applied to a set of constrained problem. The simulation results show that ASSA is an efficient algorithm for constrained optimization problems.

Keywords

constraint theory; particle swarm optimisation; search problems; artificial searching swarm algorithm; constrained optimization problems; nonparameter penalty method; penalty function method; Algorithm design and analysis; Artificial intelligence; Biological system modeling; Biological systems; Constraint optimization; Design engineering; Design optimization; Electromagnetic fields; Evolutionary computation; Reconnaissance; artificial searching swarm algorithm; bionic intellident optimization algorithm; constrained optimization problem; evolutionary algorithms; optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-4754-1

Electronic_ISBN

978-1-4244-4738-1

Type

conf

DOI

10.1109/ICICISYS.2009.5357779

Filename

5357779