Mustafa, Mamat and Mohamed, Hamoda and Mohd Rivaie, Mohd Ali (2016) A conjugate gradient method with Strong Wolfe-Powell line search for unconstrained optimization. Applied Mathematical Sciences, 10 (13). pp. 721-734. ISSN 1312885X [P]
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Abstract
In this paper, a modified conjugate gradient method is presented for solving large-scale unconstrained optimization problems, which possesses the sufficient descent property with Strong Wolfe-Powell line search. A global convergence result was proved when the (SWP) line search was used under some conditions. Computational results for a set consisting of 138 unconstrained optimization test problems showed that this new conjugate gradient algorithm seems to converge more stable and is superior to other similar methods in many situations.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | conjugate gradient coefficient, inexact line search, strong Wolfe– Powell line search, global convergence, large scale, unconstrained optimization |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Informatics & Computing |
| Depositing User: | Syahmi Manaf |
| Date Deposited: | 13 Sep 2022 05:47 |
| Last Modified: | 13 Sep 2022 05:47 |
| URI: | http://eprints.unisza.edu.my/id/eprint/7219 |
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