Abstract

A new nonlinear conjugate gradient method is proposed and analyzed. The new method reduces to the famous Dai-Yuan method when the parameter u = 0. And with the exact line search, the new method also reduces to the famous Fletcher-Reeves method when the objective function is a quadratic function. Under the strong Wolfe line search, the new method satisfies the sufficient descent condition, and its global convergence is also established. Numerical comparisons are given with the famous PRP and CG-DESCENT methods using some unconstrained optimization problems.

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