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Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization

The nonlinear conjugate gradient (CG) methods have widely been used in solving unconstrained optimization problems. They are well-suited for large-scale optimization problems due to their low memory requirements and least computational costs. In this paper, a new diagonal preconditioned conjugate gr...

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Main Authors: Ng, Choong Boon, Leong, Wah June, Monsi, Mansor
Format: Article
Language:English
Published: Universiti Putra Malaysia Press 2014
Online Access:http://psasir.upm.edu.my/id/eprint/40566/1/48.%20Diagonal%20Preconditioned%20Conjugate%20Gradient%20Algorithm%20for.pdf
http://psasir.upm.edu.my/id/eprint/40566/
http://pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2022%20(1)%20Jan.%202014/18%20Page%20213-224%20(JST%200385-2012).pdf
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spelling my.upm.eprints.405662019-10-09T08:28:00Z http://psasir.upm.edu.my/id/eprint/40566/ Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization Ng, Choong Boon Leong, Wah June Monsi, Mansor The nonlinear conjugate gradient (CG) methods have widely been used in solving unconstrained optimization problems. They are well-suited for large-scale optimization problems due to their low memory requirements and least computational costs. In this paper, a new diagonal preconditioned conjugate gradient (PRECG) algorithm is designed, and this is motivated by the fact that a pre-conditioner can greatly enhance the performance of the CG method. Under mild conditions, it is shown that the algorithm is globally convergent for strongly convex functions. Numerical results are presented to show that the new diagonal PRECG method works better than the standard CG method. Universiti Putra Malaysia Press 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/40566/1/48.%20Diagonal%20Preconditioned%20Conjugate%20Gradient%20Algorithm%20for.pdf Ng, Choong Boon and Leong, Wah June and Monsi, Mansor (2014) Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization. Pertanika Journal of Science & Technology, 22 (1). pp. 213-224. ISSN 0128-7680; ESSN: 2231-8526 http://pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2022%20(1)%20Jan.%202014/18%20Page%20213-224%20(JST%200385-2012).pdf
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The nonlinear conjugate gradient (CG) methods have widely been used in solving unconstrained optimization problems. They are well-suited for large-scale optimization problems due to their low memory requirements and least computational costs. In this paper, a new diagonal preconditioned conjugate gradient (PRECG) algorithm is designed, and this is motivated by the fact that a pre-conditioner can greatly enhance the performance of the CG method. Under mild conditions, it is shown that the algorithm is globally convergent for strongly convex functions. Numerical results are presented to show that the new diagonal PRECG method works better than the standard CG method.
format Article
author Ng, Choong Boon
Leong, Wah June
Monsi, Mansor
spellingShingle Ng, Choong Boon
Leong, Wah June
Monsi, Mansor
Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
author_facet Ng, Choong Boon
Leong, Wah June
Monsi, Mansor
author_sort Ng, Choong Boon
title Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
title_short Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
title_full Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
title_fullStr Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
title_full_unstemmed Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
title_sort diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
publisher Universiti Putra Malaysia Press
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/40566/1/48.%20Diagonal%20Preconditioned%20Conjugate%20Gradient%20Algorithm%20for.pdf
http://psasir.upm.edu.my/id/eprint/40566/
http://pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2022%20(1)%20Jan.%202014/18%20Page%20213-224%20(JST%200385-2012).pdf
_version_ 1648738109915922432
score 13.211869

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