Nonlinear conjugate gradient methods with sufficient descent properties for unconstrained optimization

Wataru Nakamura, Yasushi Narushima, Hiroshi Yabe

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


It is very important to generate a descent search direction independent of line searches in showing the global convergence of conjugate gradient methods. The method of Hager and Zhang (2005) satisfies the sufficient descent condition. In this paper, we treat two subjects. We first consider a unified formula of parameters which establishes the sufficient descent condition and follows the modification technique of Hager and Zhang. In order to show the global convergence of the conjugate gradient method with the unified formula of parameters, we define some property (say Property A). We prove the global convergence of the method with Property A. Next, we apply the unified formula to a scaled conjugate gradient method and show its global convergence property. Finally numerical results are given.

Original languageEnglish
Pages (from-to)595-619
Number of pages25
JournalJournal of Industrial and Management Optimization
Issue number3
Publication statusPublished - 2013
Externally publishedYes


  • Global convergence
  • Nonlinear conjugate gradient method
  • Scaled conjugate gradient method
  • Sufficient descent property
  • Unconstrained optimization

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management
  • Control and Optimization
  • Applied Mathematics


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