## 5 Evaluations and Comparisons with the Current Situation
To ensure transparency and reproducibility, the complete data set, including input parameters and corresponding results for all 20 scenarios, has been made publicly available at [[https://github.com/miululucak/Dynamic-Scheduling-in-Identical-Parallel-Machines-Environments](https://github.com/miululucak/Dynamic-Scheduling-in-Identical-Parallel-Machines-Environments)]([https://github.com/miululucak/Dynamic-Scheduling-in-Identical-Parallel-Machines-Environments](https://github.com/miululucak/Dynamic-Scheduling-in-Identical-Parallel-Machines-Environments)) (accessed on 21 December 2024). Readers can access the data set through this repository for further analysis and verification. As can be seen in the table, an average improvement of approximately 50 percent in TWT and 27 percent in the NTJ was observed. The main reason for this improvement is that the weight and due date parameters are specifically taken into account in the dispatching rules we use in the MIU approach. After objective function assessment, performance criteria which are given in Section 2 have been calculated. In this study, the change in the start times of jobs is considered as the stability criterion. Robustness is assessed through three metrics: the largest difference in the amount of delay as robustness1, the difference in the total amount of delay as robustness2, and the difference in the total weighted amount of delay as robustness3. Lastly, nervousness is defined as the difference between the initially planned and resulting machine job assignments. According to our definitions, lower values for stability, robustness, and nervousness indicate a positive characteristic. In Table 9, the company's current strategy and MIU approach results in terms of stability, robustness, and nervousness are given. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Scenario**} & \multicolumn{4}{c}{**TWT**} & \multicolumn{4}{c}{**NTJ**} \\ \cline{2-7}  & **Current** & **MIU** & **Approach** & **Improvement** & **Current** & **MIU** & **Approach** & **Improvement** \\ \hline
12 & 235 & 16 & 93.19\% & 7 & 3 & 57.14\% \\ \hline
13 & 322 & 164 & 49.07\% & 8 & 5 & 37.50\% \\ \hline
14 & 263 & 37 & 85.93\% & 8 & 3 & 62.50\% \\ \hline
15 & 360 & 193 & 46.39\% & 8 & 7 & 12.50\% \\ \hline
16 & 446 & 337 & 24.44\% & 17 & 10 & 41.18\% \\ \hline
17 & 457 & 245 & 46.39\% & 15 & 8 & 46.67\% \\ \hline
18 & 576 & 378 & 34.38\% & 18 & 10 & 44.44\% \\ \hline
19 & 695 & 502 & 27.77\% & 16 & 12 & 25.00\% \\ \hline
20 & 692 & 426 & 38.44\% & 15 & 11 & 26.67\% \\ \hline
**Average** & & & **48.19\%** & & & **27.10\%** \\ \hline \hline \end{tabular}
\end{table} 
Table 8: _Cont._ \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Current Method**} & \multicolumn{2}{c}{**MIU Approach**} \\ \cline{2-4}  & **Total Weighted** & **Total Tardiness** & **Total Tardy Jobs** \\  & & **Minimization** & **Minimization** \\ \hline stability & 158 & 227 & 454 \\ \hline robustness & 18 & 27 & 81 \\ \hline robustness2 & 133 & 149 & 127 \\ \hline robustness3 & 276 & 261 & 318 \\ \hline nervousness & 1 & 8 & 7 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Comparison between current method and MIU approach in terms of evaluation criteria. It is important to note that the numerical values in Table 9 present a comparative result rather than absolute quantities. For instance, doubling the stability value does not imply that the solution is twice as bad but rather indicates reduced stability. The illustrative nature of these figures is crucial in this context. These numbers could vary significantly depending on the characteristics of the data set; however, the underlying meaning of the metrics remains consistent. In the current production system, disruptions are addressed by promptly performing partial rescheduling rather than complete rescheduling, ensuring minimal changes to the remaining orders. This approach leads to better stability and nervousness values compared to the MIU approach.