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

Yasushi Narushima, Hiroshi Yabe, John A. Ford

研究成果: Article査読

71 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)212-230
ページ数19
ジャーナルSIAM Journal on Optimization
21
1
DOI
出版ステータスPublished - 2011
外部発表はい

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス

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