DocumentCode :
506557
Title :
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
Link To Document :
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