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Article: A unified framework of some proximal-based decomposition methods for monotone variational inequalities with separable structures

TitleA unified framework of some proximal-based decomposition methods for monotone variational inequalities with separable structures
Authors
KeywordsVariational inequality
Alternating
Decomposition
Parallel
Proximal point algorithm
Issue Date2012
Citation
Pacific Journal of Optimization, 2012, v. 8, n. 4, p. 817-844 How to Cite?
AbstractSome existing decomposition methods for solving a class of variational inequalities (VIs) with separable structures are closely related to the classical proximal point algorithm (PPA), as their decomposed sub-VIs are regularized by proximal terms. Differing in whether the generated sub-VIs are suitable for parallel computation, these proximal-based methods can be categorized into parallel decomposition methods and alternating decomposition methods. This paper generalizes these methods and thus presents a unified framework of proximal-based decomposition methods for solving this class of VIs, in both exact and inexact versions. Then, for various special cases of the unified framework, we analyze respective strategies for fulfilling a condition that ensures the convergence, which are realized by determining appropriate proximal parameters. Moreover, some concrete numerical algorithms for solving this class of VIs are derived. In particular, the inexact version of this unified framework gives rise to some implementable algorithms that allow the involved sub-VIs to be solved under some favorable criteria developed in PPA literature. © 2012 Yokohama Publishers.
Persistent Identifierhttp://hdl.handle.net/10722/251028
ISSN
2020 Impact Factor: 0.782

 

DC FieldValueLanguage
dc.contributor.authorHe, Bingsheng-
dc.contributor.authorYuan, Xiaoming-
dc.date.accessioned2018-02-01T01:54:22Z-
dc.date.available2018-02-01T01:54:22Z-
dc.date.issued2012-
dc.identifier.citationPacific Journal of Optimization, 2012, v. 8, n. 4, p. 817-844-
dc.identifier.issn1348-9151-
dc.identifier.urihttp://hdl.handle.net/10722/251028-
dc.description.abstractSome existing decomposition methods for solving a class of variational inequalities (VIs) with separable structures are closely related to the classical proximal point algorithm (PPA), as their decomposed sub-VIs are regularized by proximal terms. Differing in whether the generated sub-VIs are suitable for parallel computation, these proximal-based methods can be categorized into parallel decomposition methods and alternating decomposition methods. This paper generalizes these methods and thus presents a unified framework of proximal-based decomposition methods for solving this class of VIs, in both exact and inexact versions. Then, for various special cases of the unified framework, we analyze respective strategies for fulfilling a condition that ensures the convergence, which are realized by determining appropriate proximal parameters. Moreover, some concrete numerical algorithms for solving this class of VIs are derived. In particular, the inexact version of this unified framework gives rise to some implementable algorithms that allow the involved sub-VIs to be solved under some favorable criteria developed in PPA literature. © 2012 Yokohama Publishers.-
dc.languageeng-
dc.relation.ispartofPacific Journal of Optimization-
dc.subjectVariational inequality-
dc.subjectAlternating-
dc.subjectDecomposition-
dc.subjectParallel-
dc.subjectProximal point algorithm-
dc.titleA unified framework of some proximal-based decomposition methods for monotone variational inequalities with separable structures-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-84875010693-
dc.identifier.volume8-
dc.identifier.issue4-
dc.identifier.spage817-
dc.identifier.epage844-
dc.identifier.eissn1349-8169-
dc.identifier.issnl1348-9151-

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