A New Scalar of Conjugate Gradient Methods for Solving Unconstrained Minimization

In this paper, we derive a search direction for the conjugate-gradient method based on use of self-scaling Quasi Newton-method, and usefulness new is to solve unconstrained optimization problems with large dimensions. order clarify importance proposed method, have shown its characteristics in terms sufficient descent condition theoretically global convergence condition. Numerically, applied variety known test functions prove effectiveness. When compared some previous methods same direction, proved be superior them relation tools used purpose.