APPROXIMATE OPTIMALITY CONDITIONS AND MIXED TYPE DUALITY FOR COMPOSITE CONVEX OPTIMIZATION PROBLEMS

被引：0
|
作者：
Wang, Jiaolang [1 ]
Xie, Feifei [1 ]
Wang, Xianyun [1 ]
Fang, Donghui [1 ]
机构：
[1] Jishou Univ, Coll Math & Stat, Jishou 416000, Peoples R China
来源：
JOURNAL OF NONLINEAR AND CONVEX ANALYSIS | 2022年 / 23卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Composite convex optimization; constraint qualification; approximate optimality conditions; mixed type duality; CONSTRAINT QUALIFICATIONS; EQUILIBRIUM PROBLEMS; FIXED-POINT; CONVERGENCE;
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 the study of the optimality conditions and mixed type duality for composite convex optimization problems in locally convex Hausdorff topological vector spaces. By using properties of the epsilon-subdifferentials of convex functions, we introduce a new constraint qualification. Under this constraint qualification, the quasi (alpha, epsilon)-optimal solutions are characterized and the approximate duality theorems in term of mixed type are established. Applications to the conical programming and the convex infinite programming are also given.
引用
收藏
页码：755 / 768
页数：14
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