A three-term conjugate gradient method with sufficient descent property for unconstrained optimization

Yasushi Narushima, Hiroshi Yabe, John A. Ford

Research output: Contribution to journalArticlepeer-review

62 Citations (Scopus)

Abstract

Conjugate gradient methods are widely used f or solving large-scale unconstrained optimization problems because they do not need the storage of matrices. In this paper, we propose a general form of three-term conjugate gradient methods which always generate a sufficient descent direction. We give a sufficient condition for the global convergence of the proposed method. Moreover, we present a specific three-term conjugate gradient method based on the multistep quasi-Newton method. Finally, some numerical results of the proposed method are given.

Original languageEnglish
Pages (from-to)212-230
Number of pages19
JournalSIAM Journal on Optimization
Volume21
Issue number1
DOIs
Publication statusPublished - 2011

Keywords

  • Global convergence
  • Sufficient descent condition
  • Three-term conjugate gradient method
  • Unconstrained optimization

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science

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