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Novel supervisor-searcher cooperation algorithms for minimization problems with strong noise
Dai, YH; Lamb, J; Liu, WB
2003-06-01
Source PublicationOPTIMIZATION METHODS & SOFTWARE
ISSN1055-6788
Volume18Issue:3Pages:247-264
AbstractThis work continues the investigation in Ref. [1]: designing minimization algorithms in the framework of supervisor and searcher cooperation (SSC). It explores a wider range of possible supervisors and search engines to be used in the construction of SSC algorithms. Global convergence is established for algorithms with general supervisors and search engines in the absence of noise, and the convergence rate is studied. Both theoretical analysis and numerical results illustrate the appealing attributes of the proposed algorithms.
Keywordsupervisor searcher cooperation global convergence stochastic optimization stochastic approximation
DOI10.1080/1055678031000119364
Language英语
WOS Research AreaComputer Science ; Operations Research & Management Science ; Mathematics
WOS SubjectComputer Science, Software Engineering ; Operations Research & Management Science ; Mathematics, Applied
WOS IDWOS:000184134600001
PublisherTAYLOR & FRANCIS LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/18365
Collection中国科学院数学与系统科学研究院
Affiliation1.Chinese Acad Sci, Inst Computat Math & Sci Engn Comp, Beijing 100080, Peoples R China
2.Univ Kent, CBS, Canterbury CT2 7PE, Kent, England
Recommended Citation
GB/T 7714
Dai, YH,Lamb, J,Liu, WB. Novel supervisor-searcher cooperation algorithms for minimization problems with strong noise[J]. OPTIMIZATION METHODS & SOFTWARE,2003,18(3):247-264.
APA Dai, YH,Lamb, J,&Liu, WB.(2003).Novel supervisor-searcher cooperation algorithms for minimization problems with strong noise.OPTIMIZATION METHODS & SOFTWARE,18(3),247-264.
MLA Dai, YH,et al."Novel supervisor-searcher cooperation algorithms for minimization problems with strong noise".OPTIMIZATION METHODS & SOFTWARE 18.3(2003):247-264.
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