Abstract
In this paper, an entropy-like proximal method for the minimization of a convex function subject to positivity constraints is extended to an interior algorithm in two directions. First, to general linearly constrained convex minimization problems and second, to variational inequalities on polyhedra. For linear programming, numerical results are presented and quadratic convergence is established.
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Corresponding author. His research has been supported by C.E.E grants: CI1* CT 92-0046.
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Auslender, A., Haddou, M. An interior-proximal method for convex linearly constrained problems and its extension to variational inequalities. Mathematical Programming 71, 77–100 (1995). https://doi.org/10.1007/BF01592246
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DOI: https://doi.org/10.1007/BF01592246