A New Hybrid Three-Term Conjugate Gradient Algorithm for Large-Scale Unconstrained Problems

Three-term conjugate gradient methods have attracted much attention for large-scale unconstrained problems in recent years, since they attractive practical factors such as simple computation, low memory requirement, better descent property and strong global convergence property. In this paper, a hybrid three-term algorithm is proposed it owns sufficient property, independent of any line search technique. Under some mild conditions, the method globally convergent uniformly convex objective functions. Meanwhile, by using modified secant equation, also without convexity assumption on function. Numerical results indicate that more efficient reliable than other testing problems.