APPROXIMATE OPTIMALITY CONDITIONS AND MIXED TYPE DUALITY FOR QUASICONVEX OPTIMIZATION

被引：0
作者：
Wang, Junying [1 ]
Fang, Donghui [1 ]
Qiu, Lixia [1 ]
Zeng, Zhaohui [1 ]
机构：
[1] Jishou Univ, Coll Math & Stat, Jishou 416000, Peoples R China
来源：
JOURNAL OF NONLINEAR AND CONVEX ANALYSIS | 2024年 / 25卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Quasiconvex programming; approximate optimality conditions; mixed type duality; CONSTRAINT QUALIFICATIONS;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper is devoted to study the optimality conditions and mixed type duality for quasiconvex programming with constraint functions being a family of proper lower semicontinuous quasiconvex functions in locally convex Hausdorff topological vector spaces. By using the properties of the epigraph of conjugate functions and generators of involved functions, we introduce a new constraint qualification and give its equivalent characterizations. Under this new constraint qualification, the epsilon-optimal solution of quasiconvex programming are characterized and the approximate duality theorems in term of mixed type are established.
引用
收藏
页码：155 / 167
页数：13
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