In this paper, the researchers will present geometric arithmetic mean to solve non-linear fractional programming. To do this, we shall derive the inequality using the classical optimization theorem by developing the necessary and sufficient conditions for identifying the stationary points of the general inequality constraint optimization problems. Through using the geometric arithmetic mean inequality, we shall indicate how these relationships may be used to obtain the optimal solution of non-linear fractional problems. It will be observed that when the problem has a special structure, the solution may be obtained by solving a set of linear equations. Also, the numerical results are simulated by comparing geometric
arithmetic mean approach with unconstrained problems of maxima and minima approach. Several examples are presented to show the validity of the proposed approach.