A NECESSARY AND SUFFICIENT CONSTRAINT QUALIFICATION FOR SUFFICIENT OPTIMALITY CONDITIONS IN DIFFERENTIABLE PROGRAMMING

被引：0
|
作者：
Saeki, Yusuke [1 ]
Kuroiwa, Daishi [2 ]
机构：
[1] Shimane Univ, Interdisciplinary Grad Sch Sci & Engn, Matsue, Shimane, Japan
[2] Shimane Univ, Interdisciplinary Sci & Engn, Matsue, Shimane, Japan
来源：
JOURNAL OF NONLINEAR AND CONVEX ANALYSIS | 2016年 / 17卷 / 05期
关键词：
Constraint qualifications; optimality conditions; differentiable programming; differentiable multiobjective programming; generalized convexity;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we study qualifications imposed on the constraints in order to validate the Karush-Kuhn-Tucker sufficient optimality conditions in differentiable minimization programming. Such qualifications are called constraint qualifications for sufficient optimality conditions in this study. We propose a weak constraint qualification for sufficient optimality conditions, which is necessary and sufficient for the Karush-Kuhn-Tucker sufficient optimality conditions to be valid for any objective function which is pseudoconvex at the minimum point. Also, we consider differentiable multiobjective programming whose objective function is assumed some convexity condition and we show the constraint qualification is also a necessary and sufficient constraint qualification for sufficient conditions of Pareto optimality and weak Pareto optimality.
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页码：1013 / 1024
页数：12
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