DocumentCode
2333200
Title
Two-stage based ensemble optimization for large-scale global optimization
Author
Wang, Yu ; Li, Bin
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
8
Abstract
Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. In this paper, a two-stage based ensemble optimization evolutionary algorithm (EOEA) is designed to handle LSGO problems. The performance of EOEA is evaluated on the test functions provided by the LSGO competition of IEEE Congress of Evolutionary Computation (CEC 2010). Compared with some previous LSGO algorithms, EOEA demonstrates better performance.
Keywords
evolutionary computation; IEEE congress; engineering applications; evolutionary computation; large-scale global optimization; scientific applications; two-stage based ensemble optimization evolutionary algorithm; Algorithm design and analysis; Convergence; Evolutionary computation; Measurement; Optimization; Probabilistic logic; Search problems;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location
Barcelona
Print_ISBN
978-1-4244-6909-3
Type
conf
DOI
10.1109/CEC.2010.5586466
Filename
5586466
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