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Conference Paper: Forward-backward-based descent methods for composite variational inequalities

TitleForward-backward-based descent methods for composite variational inequalities
Authors
Keywordscontraction
composite mapping
descent direction
forward-backward method
variational inequality
Issue Date2013
Citation
Optimization Methods and Software, 2013, v. 28, n. 4, p. 706-724 How to Cite?
AbstractWe consider the monotone composite variational inequality (CVI) where the underlying mapping is formed as the sum of two monotone mappings. We combine the forward-backward and descent direction ideas together, and thus present the unified algorithmic framework of forward-backward-based descent methods for solving the CVI. A new iterate of such a method is generated by a prediction-correction fashion, where the predictor is yielded by the forward-backward method and then the predictor is corrected by a descent step. We derive some implementable forward-backward-based descent algorithms for some concrete cases of the CVI, and verify their numerical efficiency via preliminary numerical experiments. © 2013 Copyright Taylor and Francis Group, LLC.
Persistent Identifierhttp://hdl.handle.net/10722/250868
ISSN
2020 Impact Factor: 2.152
2020 SCImago Journal Rankings: 0.789
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHe, Bingsheng-
dc.contributor.authorYuan, Xiaoming-
dc.date.accessioned2018-02-01T01:53:56Z-
dc.date.available2018-02-01T01:53:56Z-
dc.date.issued2013-
dc.identifier.citationOptimization Methods and Software, 2013, v. 28, n. 4, p. 706-724-
dc.identifier.issn1055-6788-
dc.identifier.urihttp://hdl.handle.net/10722/250868-
dc.description.abstractWe consider the monotone composite variational inequality (CVI) where the underlying mapping is formed as the sum of two monotone mappings. We combine the forward-backward and descent direction ideas together, and thus present the unified algorithmic framework of forward-backward-based descent methods for solving the CVI. A new iterate of such a method is generated by a prediction-correction fashion, where the predictor is yielded by the forward-backward method and then the predictor is corrected by a descent step. We derive some implementable forward-backward-based descent algorithms for some concrete cases of the CVI, and verify their numerical efficiency via preliminary numerical experiments. © 2013 Copyright Taylor and Francis Group, LLC.-
dc.languageeng-
dc.relation.ispartofOptimization Methods and Software-
dc.subjectcontraction-
dc.subjectcomposite mapping-
dc.subjectdescent direction-
dc.subjectforward-backward method-
dc.subjectvariational inequality-
dc.titleForward-backward-based descent methods for composite variational inequalities-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/10556788.2011.645033-
dc.identifier.scopuseid_2-s2.0-84880238495-
dc.identifier.volume28-
dc.identifier.issue4-
dc.identifier.spage706-
dc.identifier.epage724-
dc.identifier.eissn1029-4937-
dc.identifier.isiWOS:000320925500004-
dc.identifier.issnl1026-7670-

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