AN EXTENDED DESCENT FRAMEWORK FOR VARIATIONAL-INEQUALITIES

被引：60

作者：

ZHU, DL ^{[1
]}

MARCOTTE, P ^{[1
]}

机构：

[1] UNIV MONTREAL,DEPT INFORMAT & RECH OPERAT,MONTREAL H3C 3J7,QUEBEC,CANADA

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 1994年 / 80卷 / 02期

关键词：

MATHEMATICAL PROGRAMMING; VARIATIONAL INEQUALITIES; DESCENT METHODS;

D O I：

10.1007/BF02192941

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 develop a very general descent framework for solving asymmetric, monotone variational inequalities. We introduce two classes of differentiable merit functions and the associated global convergence frameworks which include, as special instances, the projection, Newton, quasi-Newton, linear Jacobi, and nonlinear methods. The generic algorithm is very flexible and consequently well suited for exploiting any particular structure of the problem.

引用

页码：349 / 366

页数：18

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