The efficiency and practicability of a quadratic decomposition programming algorithm is compared to a direct nonlinear programming model. It is concluded that the rate of convergence of the decomposition method depends on the total number of variables in the problem, the general structure of the problem and the form of the corporate constraints, the size of the master program, and the number of the subproblems. Also, it is shown that the decomposition model is more efficient than the direct method when the total number of variables in the program exceed twenty.