A New Coefficient of the Conjugate Gradient Method with the Sufficient Descent Condition and Global Convergence Properties

Conjugate gradient methods are the most famous methods for solving unconstrained, large-scale optimization. In this article, we propose a new coefficient of the conjugate gradient method for solving unconstrained minimization problems. The new method is a modification of NPRP (2009) coefficient. The sufficient descent condition and global convergence of the new method are given under the exact line search and the strong Wolfe line search with σ ∈ (0, 1 8 ). The numerical results show that the new method has good performance in solving unconstrained minimization problems.