CASIA OpenIR  > 09年以前成果
Unified eigen analysis on multivariate Gaussian based estimation of distribution algorithms
Dong, Weishan1; Yao, Xin2
AbstractMultivariate 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.
KeywordEstimation Of Distribution Algorithm Eigen Analysis Multivariate Gaussian Distribution Covariance Matrix Scaling Eigenvalue Tuning
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems
WOS IDWOS:000257404100003
Citation statistics
Cited Times:35[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.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
Recommended Citation
GB/T 7714
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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Dong, Weishan]'s Articles
[Yao, Xin]'s Articles
Baidu academic
Similar articles in Baidu academic
[Dong, Weishan]'s Articles
[Yao, Xin]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Dong, Weishan]'s Articles
[Yao, Xin]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.