A CONSTRAINT QUALIFICATION CHARACTERIZING SURROGATE DUALITY FOR QUASICONVEX PROGRAMMING

被引：0

作者：

Suzuki, Satoshi ^{[1
]}

Kuroiwa, Daishi ^{[1
]}

机构：

[1] Shimane Univ, Dept Math, 1060 Nishikawatsu, Matsue, Shimane 6908504, Japan

来源：

PACIFIC JOURNAL OF OPTIMIZATION | 2016年 / 12卷 / 01期

关键词：

surrogate strong duality; surrogate min-max duality; quasiconvex programming; constraint qualification; OPTIMIZATION; SYSTEMS;

D O I：

暂无

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

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.

引用

页码：87 / 100

页数：14

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