Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A nonlinear conjugate gradient method based on the MBFGS secant condition

A nonlinear conjugate gradient method based on the MBFGS secant condition In this article, a new conjugate gradient method based on the MBFGS secant condition is derived, which is regarded as a modified version of Dai–Liao method or Yabe–Takano method. This method is shown to be globally convergent under some assumptions. It is new feature that the proof of global convergence of this method is very simple without proving so-called Property(*) given by Gilbert and Nocedal for general unconstrained optimization problems. Our numerical results show that this method is efficient for the given test problems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Optimization Methods and Software Taylor & Francis

A nonlinear conjugate gradient method based on the MBFGS secant condition

Optimization Methods and Software , Volume 21 (5): 8 – Oct 1, 2006
8 pages

Loading next page...
 
/lp/taylor-francis/a-nonlinear-conjugate-gradient-method-based-on-the-mbfgs-secant-1200HiwQn2

References (13)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1029-4937
eISSN
1055-6788
DOI
10.1080/10556780500137041
Publisher site
See Article on Publisher Site

Abstract

In this article, a new conjugate gradient method based on the MBFGS secant condition is derived, which is regarded as a modified version of Dai–Liao method or Yabe–Takano method. This method is shown to be globally convergent under some assumptions. It is new feature that the proof of global convergence of this method is very simple without proving so-called Property(*) given by Gilbert and Nocedal for general unconstrained optimization problems. Our numerical results show that this method is efficient for the given test problems.

Journal

Optimization Methods and SoftwareTaylor & Francis

Published: Oct 1, 2006

Keywords: Unconstrained optimization; Conjugate gradient method; Global convergence; Line search

There are no references for this article.