Abstract: The paper presents a new supermemory gradient algorithm for unconstrained minimiza-tion problems. The algorithm makes full use of the previous iterative information to generate the search direction at each iteration and uses Armijo's line search to find the stepsize. We can prove its global convergence under mild conditions.

Key words: unconstrained minimization, supermemory gradients, global con-vergence, inexact line search