DocumentCode
2794560
Title
Parallel Cat Swarm Optimization
Author
Tsai, Pei-Wei ; Pan, Jeng-Shyang ; Chen, Shyi-Ming ; Liao, Bin-Yih ; Hao, Szu-ping
Author_Institution
Dept. of Electron. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung
Volume
6
fYear
2008
fDate
12-15 July 2008
Firstpage
3328
Lastpage
3333
Abstract
We investigate a parallel structure of cat swarm optimization (CSO) in this paper, and we call it parallel cat swarm optimization (PCSO). In the experiments, we compare particle swarm optimization (PSO) with CSO and PCSO. The experimental results indicate that both CSO and PCSO perform well. Moreover, PCSO is an effective scheme to improve the convergent speed of cat swarm optimization in case the population size is small and the whole iteration is less.
Keywords
convergence; optimisation; convergent speed; parallel cat swarm optimization; particle swarm optimization; Ant colony optimization; Cats; Competitive intelligence; Computational intelligence; Computer science; Concurrent computing; Cybernetics; Machine learning; Mechanical engineering; Particle swarm optimization; Evolutionary; computational intelligence; optimization; parallel swarm; swarm intelligent;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620980
Filename
4620980
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