Differential stability of convex optimization problems under weaker conditions

被引:4
作者
Duong Thi Viet An [1 ]
Koebis, Markus A. [2 ]
Nguyen Van Tuyen [3 ]
机构
[1] Thai Nguyen Univ Sci, Dept Math & Informat, Thai Nguyen, Vietnam
[2] Free Univ Berlin, Dept Math & Comp Sci, Berlin, Germany
[3] Hanoi Pedag Univ 2, Dept Math, Phuc Yen, Vietnam
关键词
Parametric convex programming; optimal value function; subdifferentials; epsilon-subdifferentials; epsilon-normal directions; SUBDIFFERENTIAL CALCULUS; SUBGRADIENTS;
D O I
10.1080/02331934.2019.1687697
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
Differential stability properties of convex optimization problems in Hausdorff locally convex topological vector spaces are considered in this paper. We obtain new formulas for the subdifferential and the singular subdifferential of the optimal value function of convex optimization problems. Namely, instead of using the traditional Moreau-Rockafellar Theorem, we employ a sum rule for subdifferentials of two convex functions from the work of Correa, Hantoute, and Lopez [Weaker conditions for subdifferential calculus of convex functions. J Funct Anal. 2016;271:1177-1212]. Detailed comparisons with some known results are also given in this paper.
引用
收藏
页码:385 / 399
页数:15
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