Optimality conditions in optimization under uncertainty
Peer reviewed, Journal article
Accepted version
Permanent lenke
https://hdl.handle.net/11250/3141823Utgivelsesdato
2023Metadata
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- Institutt for matematiske fag [2451]
- Publikasjoner fra CRIStin - NTNU [38070]
Originalversjon
Journal of Nonlinear and Variational Analysis. 2023, 7 (5), 769-784. 10.23952/jnva.7.2023.5.07Sammendrag
Most optimization problems involve uncertain data due to measurement errors, unknown future developments, and modeling approximations. In this paper, we consider scalar optimization problems under uncertainty with infinite scenario sets. We apply methods from vector optimization in general spaces, set-valued optimization, and scalarization techniques to derive necessary optimality conditions for solutions of robust optimization problems.