An efficient new hybrid CG-method as convex combination of DY and CD and HS algorithms

In this paper, we proposed a new hybrid conjugate gradient algorithm for solving unconstrained optimization problems as convex combination of the Dai-Yuan algorithm, conjugate-descent and Hestenes-Stiefel algorithm. This is globally convergent satisfies sufficient descent condition by using strong Wolfe conditions. The numerical results show that nonlinear efficient robust.