An efficient hybrid conjugate gradient method with descent properties under strong Wolfe line search. Issue 1 (July 2021)

• Record Type: Journal Article
• Authors: Sulaiman, I M; Mamat, M; Hassan, Basim A.; Ghazali, P L; Ahmad, M Z
• Is Part Of: Journal of physics. Volume 1988:Issue 1(2021)
• Publication Date: 2021-07
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1988/1/012002
• Languages: English
• ISSNs: 1742-6588

Abstract

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 large-scale 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.