Two-stage based Ensemble Optimization for Large-Scale Global Optimization

被引：0
作者：
Wang, Yu
Li, Bin
机构：
来源：
2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2010年
关键词：
EVOLUTIONARY OPTIMIZATION; COOPERATIVE COEVOLUTION; DIFFERENTIAL EVOLUTION; SEARCH; ALGORITHM;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
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页数：8
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