The CG-BFGS method for unconstrained optimization problems

Citation

Ibrahim, Mohd Asrul Hery and Mamat, Mustafa and Leong, Wah June and Mohammad Sofi, Azfi Zaidi (2013) The CG-BFGS method for unconstrained optimization problems. In: 21st National Symposium on Mathematical Sciences (SKSM21), 6-8 Nov. 2013, Penang, Malaysia. (pp. 167-172).

Abstract

In this paper we present a new search direction known as the CG-BFGS method, which uses the search direction of the conjugate gradient method approach in the quasi-Newton methods. The new algorithm is compared with the quasi-Newton methods in terms of the number of iterations and CPU-time. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used as an updating formula for the approximation of the Hessian for both methods. Our numerical analysis provides strong evidence that our CG-BFGS method is more efficient than the ordinary BFGS method. Besides, we also prove that the new algorithm is globally convergent.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Science
DOI Number:	https://doi.org/10.1063/1.4887583
Publisher:	AIP Publishing LLC
Keywords:	BFGS method; Conjugate gradient method; Search direction
Depositing User:	Nabilah Mustapa
Date Deposited:	01 Dec 2015 02:13
Last Modified:	28 Sep 2017 02:01
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1063/1.4887583
URI:	http://psasir.upm.edu.my/id/eprint/36856
Statistic Details:	View Download Statistic

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