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

• Main Authors: Ibrahim Sulaiman, Mohammed, Puspa Liza, Ghazali, Basim A., Hassan, M.Z., Ahmad
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2021
• Subjects: QA Mathematics; QA75 Electronic computers. Computer science
• Online Access: http://eprints.unisza.edu.my/4266/1/FH03-FIK-21-56528.pdf; http://eprints.unisza.edu.my/4266/2/FH03-FIK-21-55624.pdf; http://eprints.unisza.edu.my/4266/
• Institution: Universiti Sultan Zainal Abidin

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.