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Article Dans Une Revue Mathematics of Operations Research Année : 2009

Penalty and Smoothing Methods for Convex Semi-Infinite Programming

Miguel A. Goberna
  • Fonction : Auteur
Marco A. López
  • Fonction : Auteur

Résumé

In this paper we consider min-max convex semi-infinite programming. To solve these problems we introduce a unified framework concerning Remez-type algorithms and integral methods coupled with penalty and smoothing methods. This framework subsumes well-known classical algorithms, but also provides some new methods with interesting properties. Convergence of the primal and dual sequences are proved under minimal assumptions.

Dates et versions

hal-00704915 , version 1 (06-06-2012)

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Citer

Alfred Auslender, Miguel A. Goberna, Marco A. López. Penalty and Smoothing Methods for Convex Semi-Infinite Programming. Mathematics of Operations Research, 2009, 34 (2), pp.303-319. ⟨10.1287/moor.1080.0362⟩. ⟨hal-00704915⟩
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