Robust Optimality Conditions for a Class of Fractional Optimization Problems

被引：2

作者：

Saeed, Tareq ^{[1
]}

机构：

[1] King Abdulaziz Univ, Fac Sci, Dept Math, FMAS Res Grp, Jeddah 21589, Saudi Arabia

来源：

AXIOMS | 2023年 / 12卷 / 07期

关键词：

convexity; concavity; fractional optimization problem; robust necessary optimality conditions; robust sufficient optimality conditions; robust optimal solution; PROGRAMMING PROBLEMS;

D O I：

10.3390/axioms12070673

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, by considering the parametric technique, we study a class of fractional optimization problems involving data uncertainty in the objective functional. We formulate and prove the robust Karush-Kuhn-Tucker necessary optimality conditions and provide their sufficiency by considering the convexity and/or concavity assumptions of the involved functionals. In addition, to complete the study, an illustrative example is presented.

引用

页数：13

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