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Lagrangian Approach to Quasiconvex Programing

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  • J.P. Penot

    (University of Pau)

Abstract

For a mathematical programming problem, we consider a Lagrangian approach inspired by quasiconvex duality, but as close as possible to the usual convex Lagrangian. We focus our attention on the set of multipliers and we look for their interpretation as generalized derivatives of the performance function associated with a simple perturbation of the given problem. We do not use quasiconvex dualities, but simple direct arguments.

Suggested Citation

  • J.P. Penot, 2003. "Lagrangian Approach to Quasiconvex Programing," Journal of Optimization Theory and Applications, Springer, vol. 117(3), pages 637-647, June.
    • Handle: RePEc:spr:joptap:v:117:y:2003:i:3:d:10.1023_a:1023957924086
    DOI: 10.1023/A:1023957924086
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    References listed on IDEAS

    as
    1. Jean-Paul Penot & Michel Volle, 1990. "On Quasi-Convex Duality," Mathematics of Operations Research, INFORMS, vol. 15(4), pages 597-625, November.
    2. J.P. Penot, 2003. "Characterization of Solution Sets of Quasiconvex Programs," Journal of Optimization Theory and Applications, Springer, vol. 117(3), pages 627-636, June.
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    Cited by:

    1. N. T. H. Linh & J.-P. Penot, 2012. "Generalized Affine Functions and Generalized Differentials," Journal of Optimization Theory and Applications, Springer, vol. 154(2), pages 321-338, August.

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