An efficient hybrid conjugate gradient method with descent properties under strong Wolfe line search. Issue 1 (July 2021) - Sulaiman, I M; Mamat, M; Hassan, Basim A.; Ghazali, P L; Ahmad, M Z
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.