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 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: | 2013 | |
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 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/11562/786364 | |
Appare nelle tipologie: | 07.14 Rapporti di ricerca |
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