An efficient hybrid conjugate gradient method with descent properties under strong Wolfe line search

Ibrahim Sulaiman, Mohammed and Puspa Liza, Ghazali and Basim A., Hassan and M.Z., Ahmad (2021) An efficient hybrid conjugate gradient method with descent properties under strong Wolfe line search. In: Simposium Kebangsaan Sains Matematik ke-28, 29 Jul 2021, Virtual.

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Abstract

The hybrid conjugate gradient parameters are among the efficient variants of conjugate gradient (CG) methods for solving large-scale unconstrained optimization problems. This is due to their nice convergence properties and low memory requirements. In this paper, we present a new hybrid conjugate gradient method based on famous CG algorithms for largescale unconstrained optimization. The proposed hybrid CG method can generate a descent search direction at each iteration provided the strong Wolfe line search is employed. Numerical results have been presented which show that the proposed method is efficient and promising.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Informatics & Computing
Depositing User: Fatin Safura
Date Deposited: 02 Jan 2022 04:56
Last Modified: 02 Jan 2022 04:56
URI: http://eprints.unisza.edu.my/id/eprint/4266

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