On the Iteration Complexity of Some Projection Methods for Monotone Linear Variational Inequalities

Caihua Chen, Xiaoling Fu, Bingsheng He, Xiaoming YUAN*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Projection-type methods are important for solving monotone linear variational inequalities. In this paper, we analyze the iteration complexity of two projection methods and accordingly establish their worst-case sublinear convergence rates measured by the iteration complexity in both the ergodic and nonergodic senses. Our analysis does not require any error bound condition or the boundedness of the feasible set, and it is scalable to other methods of the same kind.

Original languageEnglish
Pages (from-to)914-928
Number of pages15
JournalJournal of Optimization Theory and Applications
Volume172
Issue number3
DOIs
Publication statusPublished - 1 Mar 2017

Scopus Subject Areas

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

User-Defined Keywords

  • Convergence rate
  • Iteration complexity
  • Linear variational inequality
  • Projection methods

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