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Image Space Analysis and Separation for G-Semidifferentiable Vector Problems

Author

Listed:
  • Giandomenico Mastroeni

    (Department of Computer Science, University of Pisa, Italy)

  • Letizia Pellegrini

    (Department of Economics (University of Verona))

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.

Suggested Citation

  • Giandomenico Mastroeni & Letizia Pellegrini, 2013. "Image Space Analysis and Separation for G-Semidifferentiable Vector Problems," Working Papers 26/2013, University of Verona, Department of Economics.
    • Handle: RePEc:ver:wpaper:26/2013
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    More about this item

    Keywords

    Vector Optimization; Image Space; Separation;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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