An interior-proximal method for convex linearly constrained problems and its extension to variational inequalities

被引：69
|
作者：
Auslender, A
Haddou, M
机构：
[1] ECOLE POLYTECH, ECONOMET LAB, F-75005 PARIS, FRANCE
[2] UNIV CLERMONT FERRAND, DEPT MATH APPL, CLERMONT FERRAND, FRANCE
来源：
MATHEMATICAL PROGRAMMING | 1995年 / 71卷 / 01期
关键词：
convex linearly constrained problems; variational inequalities; interior methods; entropy-like proximal method; maximal monotone operator;
D O I：
10.1007/BF01592246
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
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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页码：77 / 100
页数：24
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