## 6 Numerical Results  
The simulation results are presented in Tables 1-3. For each scenario, the buffer size corresponding to the optimal results is indicated. The results are expressed as the percentage difference relative to the baseline MTS case, which serves as the reference point. The term 'Dynamic P' refers to the periodic review intervals tested, ranging from 100 to 25. As observed in the tables, throughput remains relatively stable across all simulated scenarios, with no significant fluctuations. To provide a more comprehensive understanding of the models' behavior, additional performance metrics are illustrated in the accompanying graphs. Figure 2 illustrates the tardiness values for exponential parameters 12, 13, and 14, expressed as a percentage difference compared to the MTS baseline. It is evident that the deviation from the MTS is smaller when the exponential parameter is set to 12. Additionally, the dynamic approach with a periodic review interval of 25 yields superior results for exponential parameters 13 and 14, demonstrating improved performance in these cases. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Optimal Buffer Size** & **3** & & **5** & **5** & **5** & **5** \\ \hline  & **MTS** & **MTO** & **Dynamic P100** & **Dynamic P50** & **Dynamic P25** &
\begin{tabular}{c} **Dynamic** \\ **Continuous** \\ \end{tabular} \\ \hline Throughput & 2049.30 & \(-0.17\%\) & \(-0.07\%\) & \(-0.03\%\) & \(-0.05\%\) & \(-0.02\%\) \\ \hline Tardiness & 32,957.19 & 218.31\% & 76.79\% & 70.65\% & 53.53\% & 61.49\% \\ \hline Earliness & 65,268.17 & \(-85.74\%\) & \(-43.68\%\) & \(-39.92\%\) & \(-31.25\%\) & \(-35.23\%\) \\ \hline Average Time in System & 72.87 & 91.42\% & 34.17\% & 31.18\% & 23.62\% & 27.11\% \\ \hline Standard Deviation of Average time in System. & 49.52 & 16.58\% & 10.50\% & 10.88\% & 9.54\% & 10.30\% \\ \hline WIP & 5.21 & \(-88.88\%\) & \(-21.02\%\) & \(-20.18\%\) & \(-15.78\%\) & \(-17.69\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation results EXPO (14). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Optimal Buffer Size** & **5** & & **5** & **5** & **5** & **5** \\ \hline  & **MTS** & **MTO** & **Dynamic P100** & **Dynamic P50** & **Dynamic P25** &
\begin{tabular}{c} **Dynamic** \\ **Continuous** \\ \end{tabular} \\ \hline Throughput & 2199.34 & \(-0.10\%\) & \(-0.09\%\) & \(-0.02\%\) & \(-0.05\%\) & \(-0.31\%\) \\ \hline Tardiness & 165,822.09 & 40.79\% & 35.17\% & 23.19\% & 28.30\% & 86.41\% \\ \hline Earliness & 45,826.35 & \(-49.88\%\) & \(-43.95\%\) & \(-33.14\%\) & \(-37.96\%\) & \(-87.26\%\) \\ \hline Average Time in System & 154.68 & 17.79\% & 14.26\% & 6.95\% & 10.10\% & 56.83\% \\ \hline Standard Deviation of the Average Time in System. & 102.49 & 8.33\% & 7.02\% & 4.03\% & 5.53\% & 14.48\% \\ \hline WIP & 17.71 & \(-48.96\%\) & \(-58.17\%\) & \(-50.21\%\) & \(-54.48\%\) & \(-84.22\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation results EXPO (13). Figure 3 presents the average time in the system for customers (AV) corresponding to exponential parameters 12, 13, and 14, shown as a percentage difference relative to the MTS baseline. The trend observed in this performance measure mirrors that of the tardiness values. However, it is noteworthy that the percentage difference between the MTS and the proposed policies is less pronounced for the AV measures compared to the tardiness, indicating that the proposed policies have a smaller impact on average time in the system than on tardiness. Figure 4 displays the standard deviation of the average time in the system for customers (Dev) for exponential parameters 12, 13, and 14, represented as a percentage difference relative to the MTS baseline. The analysis reveals that the dynamic policies effectively mitigate the increase in deviation compared to the MTS. This indicates that the dynamic approaches are successful in reducing variability in customer time in the system, leading to a more consistent performance compared to the MTS.