ANOTHER HYBRID CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS - Koontse, M.; Kaelo, P. (Journal of Nonlinear Analysis and Optimization: Theory & Applications (JNAO), 2015)
Conjugate gradient method is one of the most useful method for solving large scale unconstrained optimization problems. In this article a new hybrid conjugate gradient method that satisfies the descent condition independently of the line searches is proposed. In particular, it is a hybrid of the Fletcher-Reeves~($β_k^{FR}$) and Polak-Ribiere-Polyak~($β_k^{PRP}$) methods. Convergence analysis of the new method is presented. Numerical results of the method show that the proposed hybrid algorithm is just as competitive.