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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Vydáno v:Optimization Ročník 71; číslo 7; s. 1817 - 1837
Hlavní autoři: Wei, Hong-Zhi, Chen, Chun-Rong, Li, Sheng-Jie
Médium: Journal Article
Jazyk:angličtina
Vydáno: Philadelphia Taylor & Francis 03.07.2022
Taylor & Francis LLC
Témata:
Image space analysis
Optimization
robust optimality condition
Robustness
scalar robust optimization
Separation
ISSN:0233-1934, 1029-4945
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
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ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2020.1836636