A gradient-secant algorithm for unconstrained optimization problems is presented. The algorithm uses Armijo gradient method iterations until it reaches a region where the Newton method is more efficient, and then switches over to a secant form of operation. It is concluded that an efficient method for uncon-strained minimization has been developed, and that any convergent minimization method can be substituted for the Armijo gradient method.
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