A conjugate gradient method with descent properties under strong Wolfe line search

Mustafa, Mamat and Zull, N and Aini, N. and Shoid, S. and Ghani, N.H.A. and Mohamed, N.S. and Rivaie, M and Mamat, M. (2017) A conjugate gradient method with descent properties under strong Wolfe line search. In: 1st International Conference on Applied and Industrial Mathematics and Statistics 2017, ICoAIMS 2017;, 17 October 2017, Vistana City CentreKuantan, Pahang;.

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The conjugate gradient (CG) method is one of the optimization methods that are often used in practical applications. The continuous and numerous studies conducted on the CG method have led to vast improvements in its convergence properties and efficiency. In this paper, a new CG method possessing the sufficient descent and global convergence properties is proposed. The efficiency of the new CG algorithm relative to the existing CG methods is evaluated by testing them all on a set of test functions using MATLAB. The tests are measured in terms of iteration numbers and CPU time under strong Wolfe line search. Overall, this new method performs efficiently and comparable to the other famous methods.

Item Type: Conference or Workshop Item (Paper)
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Divisions: Faculty of Informatics & Computing
Depositing User: Muhammad Akmal Azhar
Date Deposited: 17 Nov 2020 02:33
Last Modified: 17 Nov 2020 02:33
URI: http://eprints.unisza.edu.my/id/eprint/1481

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