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Duality Principles for Optimization Problems Dealing with the Difference of Vector-Valued Convex Mappings

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  • M. Volle

    (University of Avignon)

Abstract

Using the concept of a subdifferential of a vector-valued convex mapping, we provide duality formulas for the minimization of nonconvex composite functions and related optimization problems such as the minimization of a convex function over a vectorial DC constraint.

Suggested Citation

  • M. Volle, 2002. "Duality Principles for Optimization Problems Dealing with the Difference of Vector-Valued Convex Mappings," Journal of Optimization Theory and Applications, Springer, vol. 114(1), pages 223-241, July.
    • Handle: RePEc:spr:joptap:v:114:y:2002:i:1:d:10.1023_a:1015424423727
    DOI: 10.1023/A:1015424423727
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    References listed on IDEAS

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    1. R. Horst & N. V. Thoai, 1999. "DC Programming: Overview," Journal of Optimization Theory and Applications, Springer, vol. 103(1), pages 1-43, October.
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    Cited by:

    1. Ivan Ginchev & Denitza Gintcheva, 2013. "Characterization and recognition of d.c. functions," Journal of Global Optimization, Springer, vol. 57(3), pages 633-647, November.
    2. Abdelghali Ammar & Mohamed Laghdir & Ahmed Ed-dahdah & Mohamed Hanine, 2023. "Approximate Subdifferential of the Difference of Two Vector Convex Mappings," Mathematics, MDPI, vol. 11(12), pages 1-14, June.
    3. N. Dinh & G. Vallet & M. Volle, 2014. "Functional inequalities and theorems of the alternative involving composite functions," Journal of Global Optimization, Springer, vol. 59(4), pages 837-863, August.
    4. R. I. Boţ & S. M. Grad & G. Wanka, 2007. "New Constraint Qualification and Conjugate Duality for Composed Convex Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 135(2), pages 241-255, November.

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