Development a Special Conjugate Gradient Algorithm for Solving Unconstrained Minimization Problems

This paper develops a special conjugate gradient algorithm for solving unconstrained minimized problems. This development can be regarded as some kind of convex combination of the MPR and MLS methods. Experimental results indicate that the new algorithm is more efficient than the Polak and Ribiere - algorithm.