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EnglishThis paper aims at studying, in the image space, an approximation of a vector optimization problem obtained by substituting the involved functions with their G-derivatives. It is shown that, under the hypothesis of G-differentiability, the existence of a lower semistationary point is equivalent to the linear separation between the image of the approximated problem and a suitable convex subset of the image space. Applications to optimality conditions are provided.
| Titolo: | Image space analysis and separation for G-semidifferentiable vector problems |
| Autori: | |
| Data di pubblicazione: | 2015 |
| Rivista: | |
| Abstract: | This paper aims at studying, in the image space, an approximation of a vector optimization problem obtained by substituting the involved functions with their G-derivatives. It is shown that, under the hypothesis of G-differentiability, the existence of a lower semistationary point is equivalent to the linear separation between the image of the approximated problem and a suitable convex subset of the image space. Applications to optimality conditions are provided. |
| Handle: | http://hdl.handle.net/11562/837964 |
| Appare nelle tipologie: | 01.01 Articolo in Rivista |
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