A GENERAL DESCENT FRAMEWORK FOR THE MONOTONE VARIATIONAL INEQUALITY PROBLEM

被引:61
|
作者
WU, JH
FLORIAN, M
MARCOTTE, P
机构
[1] Centre de recherche sur les transports, Université de Montréal, Succursale, Montréal, H3C 3J7, Qué.
关键词
VARIATIONAL INEQUALITIES; DESCENT METHODS; OPTIMIZATION;
D O I
10.1007/BF01582152
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
We present a framework for descent algorithms that solve the monotone variational inequality problem VIP(v) which consists in finding a solution v* is-an-element-of OMEGA(v) satisfying s(v*)T(v - v* ) greater-than-or-equal-to 0, for all v is-an-element-of OMEGA(v). This unified framework includes, as special cases, some well known iterative methods and equivalent optimization formulations. A descent method is developed for an equivalent general optimization formulation and a proof of its convergence is given. Based on this unified logarithmic framework, we show that a variant of the descent method where each subproblem is only solved approximately is globally convergent under certain conditions.
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页码:281 / 300
页数:20
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