Characterizations of robust optimality conditions via image space analysis

被引：12

作者：

Ansari, Q. H. ^{[1
,2
]}

Sharma, P. K. ^{[1
,3
,4
]}

Qin, X. ^{[5
]}

机构：

[1] Aligarh Muslim Univ, Dept Math, Aligarh, Uttar Pradesh, India

[2] King Fahd Univ Petr & Minerals, Dept Math & Stat, Dhahran, Saudi Arabia

[3] Natl Sun Yat Sen Univ, Dept Appl Math, Kaohsiung, Taiwan

[4] China Med Univ, Ctr Gen Educ, Taichung, Taiwan

[5] Hangzhou Normal Univ, Dept Math, Hangzhou, Zhejiang, Peoples R China

来源：

OPTIMIZATION | 2020年 / 69卷 / 09期

关键词：

Robust optimality conditions; nonlinear scalarization; image space analysis; uncertain optimization; shortest path problem; UNCERTAIN MULTIOBJECTIVE OPTIMIZATION; VARIATIONAL-INEQUALITIES; EFFICIENCY;

D O I：

10.1080/02331934.2020.1728269

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：

In this paper, we consider general scalar robust optimization problems and study the characterizations for optimality conditions in the general vector spaces where we do not require any topology on the considered space. By using the image space analysis and nonlinear separation function, we derive some necessary and sufficient optimality conditions, especially saddle point sufficient optimality conditions for scalar robust optimization problems. Moreover, we discuss the validity and effectiveness of our results for the shortest path problem.

引用

页码：2063 / 2083

页数：21

共 22 条

[1] Weak efficiency in vector optimization using a closure of algebraic type under cone-convexlikeness [J].