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Unified eigen analysis on multivariate Gaussian based estimation of distribution algorithms
Dong, Weishan1; Yao, Xin2
2008-08-01
发表期刊INFORMATION SCIENCES
卷号178期号:15页码:3000-3023
文章类型Article
摘要Multivariate Gaussian models are widely adopted in continuous estimation of distribution algorithms (EDAs), and covariance matrix plays the essential role in guiding the evolution. In this paper, we propose a new framework for multivariate Gaussian based EDAs (MGEDAs), named eigen decomposition EDA (ED-EDA). Unlike classical EDAs, ED-EDA focuses on eigen analysis of the covariance matrix, and it explicitly tunes the eigenvalues. All existing MGEDAs can be unified within our ED-EDA framework by applying three different eigenvalue tuning strategies. The effects of eigenvalue on influencing the evolution are investigated through combining maximum likelihood estimates of Gaussian model with each of the eigenvalue tuning strategies in ED-EDA. In our experiments, proper eigenvalue tunings show high efficiency in solving problems with small population sizes, which are difficult for classical MGEDA adopting maximum likelihood estimates alone. Previously developed covariance matrix repairing (CMR) methods focusing on repairing computational errors of covariance matrix can be seen as a special eigenvalue tuning strategy. By using the ED-EDA framework, the computational time of CMR methods can be reduced from cubic to linear. Two new efficient CMR methods are proposed. Through explicitly tuning eigenvalues, ED-EDA provides a new approach to develop more efficient Gaussian based EDAs. (c) 2008 Elsevier Inc. All rights reserved.
关键词Estimation Of Distribution Algorithm Eigen Analysis Multivariate Gaussian Distribution Covariance Matrix Scaling Eigenvalue Tuning
WOS标题词Science & Technology ; Technology
关键词[WOS]OPTIMIZATION
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Information Systems
WOS记录号WOS:000257404100003
引用统计
被引频次:35[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9676
专题09年以前成果
作者单位1.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100190, Peoples R China
2.Univ Birmingham, Sch Comp Sci, CERCIA, Birmingham B15 2TT, W Midlands, England
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Dong, Weishan,Yao, Xin. Unified eigen analysis on multivariate Gaussian based estimation of distribution algorithms[J]. INFORMATION SCIENCES,2008,178(15):3000-3023.
APA Dong, Weishan,&Yao, Xin.(2008).Unified eigen analysis on multivariate Gaussian based estimation of distribution algorithms.INFORMATION SCIENCES,178(15),3000-3023.
MLA Dong, Weishan,et al."Unified eigen analysis on multivariate Gaussian based estimation of distribution algorithms".INFORMATION SCIENCES 178.15(2008):3000-3023.
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