An Extended Dai–liao Conjugate Gradient Method with Global Convergence for Nonconvex Functions

Using an extension of some previously proposed modified secant equations in the Dai–Liao approach, a modified nonlinear conjugate gradient method is proposed. As interesting features, the method employs the objective function values in addition to the gradient information and satisfies the sufficient descent property with proper choices for its parameter. Global convergence of the method is established without convexity assumption on the objective function. Results of numerical comparisons are reported. They demonstrate efficiency of the proposed method in the sense of the Dolan–Moré performance profile.