Convergent algorithm based on progressive regularization for solving pseudomonotone variational inequalities

被引:13
|
作者
El Farouq, N [1 ]
机构
[1] Univ Clermont Ferrand, Toulouse, France
[2] CNRS, LAAS, F-31077 Toulouse, France
关键词
variational inequalities; generalized monotonicity; pseudomonotonicity; regularization; convergence of algorithms; decomposition;
D O I
10.1023/B:JOTA.0000025706.49562.08
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
In this paper, we extend the Moreau-Yosida regularization of monotone variational inequalities to the case of weakly monotone and pseudomonotone operators. With these properties, the regularized operator satisfies the pseudo-Dunn property with respect to any solution of the variational inequality problem. As a consequence, the regularized version of the auxiliary problem algorithm converges. In this case, when the operator involved in the variational inequality problem is Lipschitz continuous (a property stronger than weak monotonicity) and pseudomonotone, we prove the convergence of the progressive regularization algorithm introduced in Refs. 1, 2.
引用
收藏
页码:455 / 485
页数:31
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