A New Two-Parameter Family of Nonlinear Conjugate Gradient Method Without Line Search for Unconstrained Optimization Problem

This paper puts forward a two-parameter family of nonlinear conjugate gradient (CG) method without line search for solving unconstrained optimization problem. The main feature of this method is that it does not rely on any line search and only requires a simple step size formula to always generate a sufficient descent direction. Under certain assumptions, the proposed method is proved to possess global convergence. Finally, our method is compared with other potential methods. A large number of numerical experiments show that our method is more competitive and effective.