Year: 2021
Author: P. Mtagulwa, P. Kaelo
East Asian Journal on Applied Mathematics, Vol. 11 (2021), Iss. 2 : pp. 421–434
Abstract
Conjugate gradient algorithms are most commonly used to solve large scale unconstrained optimisation problems. They are simple and do not require the computation and/or storage of the second derivative information about the objective function. We propose a new conjugate gradient method and establish its global convergence under suitable assumptions. Numerical examples demonstrate the efficiency and effectiveness of our method.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.140720.251220
East Asian Journal on Applied Mathematics, Vol. 11 (2021), Iss. 2 : pp. 421–434
Published online: 2021-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 14
Keywords: Global convergence conjugate gradient method sufficient descent strong Wolfe conditions.
Author Details
-
A convergent hybrid three-term conjugate gradient method with sufficient descent property for unconstrained optimization
Diphofu, T. | Kaelo, P. | Tufa, A.R.Topological Algebra and its Applications, Vol. 10 (2022), Iss. 1 P.47
https://doi.org/10.1515/taa-2022-0112 [Citations: 1] -
A modified nonlinear conjugate gradient algorithm for unconstrained optimization and portfolio selection problems
Diphofu, Thamiso | Kaelo, Professor | Tufa, Abebe R.RAIRO - Operations Research, Vol. 57 (2023), Iss. 2 P.817
https://doi.org/10.1051/ro/2023037 [Citations: 2]