A constraint qualification characterizing surrogate duality for quasiconvex programming

Pacific Journal of Optimization Volume 12 Issue 1 Page 87-100 published_at 2016-01

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Title	A constraint qualification characterizing surrogate duality for quasiconvex programming
Creator	Suzuki Satoshi Kuroiwa Daishi
Source Title	Pacific Journal of Optimization
Volume	12
Issue	1
Start Page	87
End Page	100
Journal Identifire	ISSN 13489151
Descriptions	In this paper, we study a constraint qualification which completely characterizes surrogate duality for quasiconvex programming. We show that the closed cone constraint qualification for surrogate duality is a necessary and sufficient constraint qualification for surrogate strong duality and surrogate min-max duality via quasiconvex programming with convex constraints. Also, we compare our constraint qualification with previous ones for Lagrange duality and surrogate duality.
Subjects	surrogate strong duality ( Other) surrogate min-max duality ( Other) quasiconvex programming ( Other) constraint qualification ( Other)
Language	eng
Resource Type	journal article
Publisher	Yokohama Publishers
Date of Issued	2016-01
Rights	Copyright © 2016 Yokohama Publishers
Publish Type	Accepted Manuscript
Access Rights	restricted access
Relation	isVersionOf [URI] http://www.yokohamapublishers.jp/online2/oppjo/vol12/p87.html isVersionOf
Remark	本誌はYokohama Publishersの電子ジャーナルサイトから冊子体発行後、一定期間を設けて無料で公開されます。