A Variant Hybrid Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization

Abstract

In this paper, we have presented a new hybrid conjugate gradient algorithm for solving unconstrained optimization problems.The parameter β is a convex combination of the PRP and FR conjugate gradient methods.Under general wolfe line search conditions, we proved the global convergence of the algorithm.The numerical results show that the proposed methods are effective.