A family of three-term conjugate gradient methods with sufficient descent property for unconstrained optimization

Mehiddin Al-Baali, Yasushi Narushima, Hiroshi Yabe

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Recently, conjugate gradient methods, which usually generate descent search directions, are useful for large-scale optimization. Narushima et al. (SIAM J Optim 21:212–230, 2011) have proposed a three-term conjugate gradient method which satisfies a sufficient descent condition. We extend this method to two parameters family of three-term conjugate gradient methods which can be used to control the magnitude of the directional derivative. We show that these methods converge globally and work well for suitable choices of the parameters. Numerical results are also presented.

Original languageEnglish
Pages (from-to)89-110
Number of pages22
JournalComputational Optimization and Applications
Volume60
Issue number1
DOIs
Publication statusPublished - 2014

Fingerprint

Conjugate gradient method
Unconstrained Optimization
Conjugate Gradient Method
Descent
Sufficient
Term
Large-scale Optimization
Directional derivative
Two Parameters
Derivatives
Converge
Numerical Results
Family

Keywords

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

ASJC Scopus subject areas

  • Applied Mathematics
  • Computational Mathematics
  • Control and Optimization

Cite this

A family of three-term conjugate gradient methods with sufficient descent property for unconstrained optimization. / Al-Baali, Mehiddin; Narushima, Yasushi; Yabe, Hiroshi.

In: Computational Optimization and Applications, Vol. 60, No. 1, 2014, p. 89-110.

Research output: Contribution to journalArticle

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