A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization

In this paper, we suggest a new nonlinear conjugate gradient method for solving large scale unconstrained optimization problems. We prove that the new conjugate gradient coefficient β k with exact line search is globally convergent. Preliminary numerical results with a set of 116 unconstrained optim...

Full description

Saved in:

Bibliographic Details
Main Authors:	Mustafa, Mamat, Mohamed, Hamoda, Mohd, Rivaie
Format:	Article
Language:	English English
Published:	HIKARI Ltd. 2015
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://eprints.unisza.edu.my/6232/1/FH02-FIK-15-03336.pdf http://eprints.unisza.edu.my/6232/2/FH02-FIK-15-03431.jpg http://eprints.unisza.edu.my/6232/
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Universiti Sultan Zainal Abidin
Language:	English English

id	my-unisza-ir.6232
record_format	eprints
spelling	my-unisza-ir.62322022-09-13T05:18:03Z http://eprints.unisza.edu.my/6232/ A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization Mustafa, Mamat Mohamed, Hamoda Mohd, Rivaie QA75 Electronic computers. Computer science In this paper, we suggest a new nonlinear conjugate gradient method for solving large scale unconstrained optimization problems. We prove that the new conjugate gradient coefficient β k with exact line search is globally convergent. Preliminary numerical results with a set of 116 unconstrained optimization problems show that β k is very promising and efficient when compared to the other conjugate gradient coefficients Fletcher - Reeves (FR) and Polak -Ribiere – Polyak (PRP). HIKARI Ltd. 2015 Article PeerReviewed text en http://eprints.unisza.edu.my/6232/1/FH02-FIK-15-03336.pdf image en http://eprints.unisza.edu.my/6232/2/FH02-FIK-15-03431.jpg Mustafa, Mamat and Mohamed, Hamoda and Mohd, Rivaie (2015) A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization. Applied Mathematical Sciences, 9 (37). pp. 1813-1822. ISSN 0066-5452 [P]
institution	Universiti Sultan Zainal Abidin
building	UNISZA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Sultan Zainal Abidin
content_source	UNISZA Institutional Repository
url_provider	https://eprints.unisza.edu.my/
language	English English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Mustafa, Mamat Mohamed, Hamoda Mohd, Rivaie A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
description	In this paper, we suggest a new nonlinear conjugate gradient method for solving large scale unconstrained optimization problems. We prove that the new conjugate gradient coefficient β k with exact line search is globally convergent. Preliminary numerical results with a set of 116 unconstrained optimization problems show that β k is very promising and efficient when compared to the other conjugate gradient coefficients Fletcher - Reeves (FR) and Polak -Ribiere – Polyak (PRP).
format	Article
author	Mustafa, Mamat Mohamed, Hamoda Mohd, Rivaie
author_facet	Mustafa, Mamat Mohamed, Hamoda Mohd, Rivaie
author_sort	Mustafa, Mamat
title	A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
title_short	A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
title_full	A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
title_fullStr	A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
title_full_unstemmed	A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
title_sort	new nonlinear conjugate gradient coefficient for unconstrained optimization
publisher	HIKARI Ltd.
publishDate	2015
url	http://eprints.unisza.edu.my/6232/1/FH02-FIK-15-03336.pdf http://eprints.unisza.edu.my/6232/2/FH02-FIK-15-03431.jpg http://eprints.unisza.edu.my/6232/
_version_	1744358549120614400

A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization

Similar Items