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Globally Convergent Three-Term Conjugate Gradient Methods that Use Secant Conditions and Generate Descent Search Directions for Unconstrained Optimization

  • Kaori Sugiki
  • Yasushi Narushima
  • Hiroshi Yabe
Article

Abstract

In this paper, we propose a three-term conjugate gradient method based on secant conditions for unconstrained optimization problems. Specifically, we apply the idea of Dai and Liao (in Appl. Math. Optim. 43: 87–101, 2001) to the three-term conjugate gradient method proposed by Narushima et al. (in SIAM J. Optim. 21: 212–230, 2011). Moreover, we derive a special-purpose three-term conjugate gradient method for a problem, whose objective function has a special structure, and apply it to nonlinear least squares problems. We prove the global convergence properties of the proposed methods. Finally, some numerical results are given to show the performance of our methods.

Keywords

Unconstrained optimization Three-term conjugate gradient method Secant condition Descent search direction Global convergence 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Mizuho Information & Research Institute, Inc.Bunkyo-kuJapan
  2. 2.Department of Communication and Information ScienceFukushima National College of TechnologyFukushimaJapan
  3. 3.Department of Mathematical Information ScienceTokyo University of ScienceTokyoJapan

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