ON SOLUTION SETS FOR ROBUST OPTIMIZATION PROBLEMS

被引：0

作者：

Lee, Gue Myung ^{[1
]}

Yao, Jen-Chih ^{[2
,3
]}

机构：

[1] Pukyong Natl Univ, Dept Appl Math, Busan 48513, South Korea

[2] China Med Univ, Ctr Gen Educ, Taichung 40402, Taiwan

[3] China Med Univ Hosp, Res Ctr Interneural Comp, Taichung 40447, Taiwan

来源：

JOURNAL OF NONLINEAR AND CONVEX ANALYSIS | 2016年 / 17卷 / 05期

基金：

新加坡国家研究基金会;

关键词：

Robust optimization problem; Lagrangian multipliers; locally Lipschitz functions; generalized gradients; generalized directional derivative; Pseudo convex function; convex function; solution sets; GENERALIZED-GRADIENTS; CONVEX-PROGRAMS; OPTIMALITY; DUALITY;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A nonsmooth optimization problem with data uncertainty, which consists of a pseudo-convex locally Lipschitz objective function and convex constraint constraint functions, is considered. The problem has been called the robust optimization problem, which has been intensively studied by many authors. The aim of this brief note is to give the Lagrange multiplier characterization of the solution set of the problem. We characterize the solution set of the problem when we know one solution of the one and its Lagrangian multipliers.

引用

页码：957 / 966

页数：10

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