An LQP-based decomposition method for solving a class of variational inequalities

Xiaoming YUAN*, Min Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

The alternating direction method (ADM) is an influential decomposition method for solving a class of variational inequalities with block-separable structures. In the literature, the subproblems of the ADM are usually regularized by quadratic proximal terms to ensure a more stable and attractive numerical performance. In this paper, we propose to apply the logarithmicquadratic proximal (LQP) terms to regularize the ADMsubproblems, and thus develop an LQP-based decomposition method for solving a class of variational inequalities. Global convergence of the new method is proved under standard assumptions.

Original languageEnglish
Pages (from-to)1309-1318
Number of pages10
JournalSIAM Journal on Optimization
Volume21
Issue number4
DOIs
Publication statusPublished - 2011

Scopus Subject Areas

  • Software
  • Theoretical Computer Science

User-Defined Keywords

  • Alternating direction method
  • Complementarity problem
  • Logarithmic-quadratic proximal method
  • System of nonlinear equations
  • Variational inequality

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