Fig. 4 shows the 3D outcome for M = 751 iterations and 

![0_image_0.png](0_image_0.png)

![0_image_1.png](0_image_1.png)

Fig. 5 shows the linear approximation for G with respect to 

![0_image_2.png](0_image_2.png) iterations 748 to 751. It can be seen that as the iterations are increased, the values of the objective function decrease. The percentage error is minimum at iteration, M = 748; however, after that it increases until it peaks at M = 750; thereafter, the percentage error decreases again to a level lower than that at M = 748. This shows that the maximum number of iterations that can be used for similar cases in the future can be limited to M = 750. Figs. 6, 7 and 8 show the linear approximation for the decision variables x1, x2 and x3 with respect to the number of iterations. It can be observed that x1, x2 and x3 decrease as the iterations are increased from M = 748 to M = 751. 

Table II presents results that involve α1 , α 2 and α 3 with M
= 748 for G, x1, x2 and x3. Other results for M = 749 to 751 are given in the appendix. 