Hölder Error Bounds and Hölder Calmness with Applications to Convex Semi-infinite Optimization

被引：0
|
作者：
Alexander Y. Kruger
Marco A. López
Xiaoqi Yang
Jiangxing Zhu
机构：
[1] Centre for Informatics and Applied Optimization,Department of Mathematics
[2] Federation University Australia,Department of Applied Mathematics
[3] University of Alicante,Department of Mathematics
[4] The Hong Kong Polytechnic University,undefined
[5] Yunnan University,undefined
来源：
Set-Valued and Variational Analysis | 2019年 / 27卷
关键词：
Hölder error bounds; Hölder calmness; Convex programming; Semi-infinite programming; 49J53; 90C25; 90C31; 90C34;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Using techniques of variational analysis, necessary and sufficient subdifferential conditions for Hölder error bounds are investigated and some new estimates for the corresponding modulus are obtained. As an application, we consider the setting of convex semi-infinite optimization and give a characterization of the Hölder calmness of the argmin mapping in terms of the level set mapping (with respect to the objective function) and a special supremum function. We also estimate the Hölder calmness modulus of the argmin mapping in the framework of linear programming.
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页码：995 / 1023
页数：28
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