当前位置: X-MOL 学术Optimization › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Robust approximate optimal solutions for nonlinear semi-infinite programming with uncertainty
Optimization ( IF 2.2 ) Pub Date : 2020-05-04 , DOI: 10.1080/02331934.2020.1763990
Xiangkai Sun 1 , Kok Lay Teo 2, 3 , Jing Zeng 1 , Liying Liu 1
Affiliation  

In this paper, we deal with robust approximate quasi optimal solutions for a class of nonlinear semi-infinite programming with data uncertainty in both the objective and constraints. By using a new robust-type subdifferential constraint qualification and some generalized convexity assumptions, we first establish approximate optimality conditions for robust approximate quasi optimal solutions of . Then, we introduce a Mixed-type robust approximate dual problem for and investigate robust approximate duality relations between them. Furthermore, we establish a nonsmooth robust approximate saddle point theorem for an uncertain approximate Lagrangian function associated with .

中文翻译:

具有不确定性的非线性半无限规划的鲁棒近似最优解

在本文中,我们处理一类具有目标和约束数据不确定性的非线性半无限规划的鲁棒近似准最优解。通过使用新的鲁棒型次微分约束条件和一些广义凸性假设,我们首先为 的鲁棒近似拟最优解建立近似最优条件。然后,我们引入了一个混合型鲁棒近似对偶问题,并研究了它们之间的鲁棒近似对偶关系。此外,我们为与 相关的不确定近似拉格朗日函数建立了一个非光滑鲁棒近似鞍点定理。
更新日期:2020-05-04
down
wechat
bug