Necessary optimality conditions for nonsmooth robust optimization problems

In this paper, we investigate robust necessary optimality for scalar uncertain optimization problems under the strictly robust counterpart, where the uncertainties are included in the objective and the constraints. Based on generalized differentiable assumptions, some robust necessary conditions via...

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Bibliographic Details
Published in:	Optimization Vol. 71; no. 7; pp. 1817 - 1837
Main Authors:	Wei, Hong-Zhi, Chen, Chun-Rong, Li, Sheng-Jie
Format:	Journal Article
Language:	English
Published:	Philadelphia Taylor & Francis 03.07.2022 Taylor & Francis LLC
Subjects:	Image space analysis Optimization robust optimality condition Robustness scalar robust optimization Separation
ISSN:	0233-1934, 1029-4945
Online Access:	Get full text
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Summary:	In this paper, we investigate robust necessary optimality for scalar uncertain optimization problems under the strictly robust counterpart, where the uncertainties are included in the objective and the constraints. Based on generalized differentiable assumptions, some robust necessary conditions via a separation scheme are derived. Besides, by means of strong separation functions, several characterizations of robust necessary optimality can be established. Finally, an example is given to show the effectiveness of the results derived in this paper.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	0233-1934 1029-4945
DOI:	10.1080/02331934.2020.1836636