A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula

The conjugate gradient and Quasi-Newton methods have advantages and drawbacks, as although quasi-Newton algorithm has more rapid convergence than conjugate gradient, they require more storage compared to conjugate gradient algorithms. In 1976, Buckley designed a method that combines the CG method wi...

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Main Authors: Mardeen Sh. Taher, Salah G. Shareef
Format: Article
Language:English
Published: Etamaths Publishing 2023-04-01
Series:International Journal of Analysis and Applications
Online Access:http://etamaths.com/index.php/ijaa/article/view/2763
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author Mardeen Sh. Taher
Salah G. Shareef
author_facet Mardeen Sh. Taher
Salah G. Shareef
author_sort Mardeen Sh. Taher
collection DOAJ
description The conjugate gradient and Quasi-Newton methods have advantages and drawbacks, as although quasi-Newton algorithm has more rapid convergence than conjugate gradient, they require more storage compared to conjugate gradient algorithms. In 1976, Buckley designed a method that combines the CG method with QN updates, which is better than that observed for conjugate gradient algorithms but not as good as the quasi-Newton approach. This type of method is called the preconditioned conjugate gradient (PCG) method. In this paper, we introduce two new preconditioned conjugate gradient (PCG) methods that combine conjugate gradient with a new update of quasi-Newton methods. The new quasi-Newton method satisfied the positive define, and the direction of the new preconditioned conjugate gradient is descent direction. In numerical results, it is showing the new preconditioned conjugate gradient method is more effective on several high-dimension test problems than standard preconditioning.
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spelling doaj.art-b0f4cc9616db4e3e9eaeb9163d863c8d2023-06-25T06:29:47ZengEtamaths PublishingInternational Journal of Analysis and Applications2291-86392023-04-0121313110.28924/2291-8639-21-2023-312148A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS FormulaMardeen Sh. TaherSalah G. ShareefThe conjugate gradient and Quasi-Newton methods have advantages and drawbacks, as although quasi-Newton algorithm has more rapid convergence than conjugate gradient, they require more storage compared to conjugate gradient algorithms. In 1976, Buckley designed a method that combines the CG method with QN updates, which is better than that observed for conjugate gradient algorithms but not as good as the quasi-Newton approach. This type of method is called the preconditioned conjugate gradient (PCG) method. In this paper, we introduce two new preconditioned conjugate gradient (PCG) methods that combine conjugate gradient with a new update of quasi-Newton methods. The new quasi-Newton method satisfied the positive define, and the direction of the new preconditioned conjugate gradient is descent direction. In numerical results, it is showing the new preconditioned conjugate gradient method is more effective on several high-dimension test problems than standard preconditioning.http://etamaths.com/index.php/ijaa/article/view/2763
spellingShingle Mardeen Sh. Taher
Salah G. Shareef
A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
International Journal of Analysis and Applications
title A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
title_full A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
title_fullStr A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
title_full_unstemmed A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
title_short A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
title_sort combined conjugate gradient quasi newton method with modification bfgs formula
url http://etamaths.com/index.php/ijaa/article/view/2763
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