Some proximal algorithms for linearly constrained general variational inequalities

M. Li, Xiaoming YUAN

Research output: Contribution to journalJournal articlepeer-review

Abstract

Based on the classical proximal point algorithm (PPA), some PPA-based numerical algorithms for general variational inequalities (GVIs) have been developed recently. Inspired by these algorithms, in this article we propose some proximal algorithms for solving linearly constrained GVIs (LCGVIs). The resulted subproblems are regularized proximally, and they are allowed to be solved either exactly or approximately.

Original languageEnglish
Pages (from-to)505-524
Number of pages20
JournalOptimization
Volume61
Issue number5
DOIs
Publication statusPublished - May 2012

Scopus Subject Areas

  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics

User-Defined Keywords

  • general variational inequality
  • inexact methods
  • linear constraint
  • proximal point algorithm

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