Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65424
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorMeng, Ken_US
dc.creatorYang, Xen_US
dc.date.accessioned2017-05-22T02:08:35Z-
dc.date.available2017-05-22T02:08:35Z-
dc.identifier.issn1877-0533en_US
dc.identifier.urihttp://hdl.handle.net/10397/65424-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© Springer Science+Business Media Dordrecht 2016en_US
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11228-016-0360-0en_US
dc.subjectExact penalizationen_US
dc.subjectLocal sharp minimumen_US
dc.subjectRegular subdifferentialen_US
dc.subjectSmallest penalty parameteren_US
dc.subjectSubderivativeen_US
dc.titleVariational analysis on local sharp minima via exact penalizationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage619en_US
dc.identifier.epage635en_US
dc.identifier.volume24en_US
dc.identifier.issue4en_US
dc.identifier.doi10.1007/s11228-016-0360-0en_US
dcterms.abstractIn this paper we study local sharp minima of the nonlinear programming problem via exact penalization. Utilizing generalized differentiation tools in variational analysis such as subderivatives and regular subdifferentials, we obtain some primal and dual characterizations for a penalty function associated with the nonlinear programming problem to have a local sharp minimum. These general results are then applied to the ?p penalty function with 0 ? p ? 1. In particular, we present primal and dual equivalent conditions in terms of the original data of the nonlinear programming problem, which guarantee that the ?p penalty function has a local sharp minimum with a finite penalty parameter in the case of p?(12,1] and p=12 respectively. By assuming the Guignard constraint qualification (resp. the generalized Guignard constraint qualification), we also show that a local sharp minimum of the nonlinear programming problem can be an exact local sharp minimum of the ?p penalty function with p ? [0, 1] (resp. p?[0,12]). Finally, we give some formulas for calculating the smallest penalty parameter for a penalty function to have a local sharp minimum.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSet-valued and variational analysis, Dec. 2016, v. 24, no. 4, p. 619-635en_US
dcterms.isPartOfSet-valued and variational analysisen_US
dcterms.issued2016-12-
dc.identifier.isiWOS:000393231300007-
dc.identifier.scopus2-s2.0-84994509059-
dc.identifier.ros2016000198-
dc.source.typeArticle-
dc.identifier.eissn1877-0541en_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberAMA-0535-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6693557-
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