## 5 Discussion of the Results  
This section discusses the results obtained from the computational examples carried out in Section 4 above. In Table 8, the baseline durations for projects A, B, and C are 14 days, 32 days, and 70 days, respectively, representing the project durations with no resource constraints. When we scheduled the projects using single-skilled resource scheduling (SSRS) software _RESCON_, the project durations increased to 20 days, 49 days, and 120 days for projects A, B, and C, respectively. However, using the existing MSRS model considering resource constraints, the project durations for projects A, B and C were reduced to 18 days, 35 days, and 78 days for projects A, B, and C, respectively. These values correspond with the solution obtained in the previous studies. More so, considering risk and uncertainty using the SMSRS model, the optimized SMSRS durations became 19.49 days, 38.12 days, and 85.77 days for projects A, B, and C, respectively, which represent the expected project durations.  
Additionally, from Table 9 it can be observed that both MSRS and SMSRS project delays are less compare to the SSRS duration. But, when the SMSRS schedule is compared with the existing MSRS result the difference of 1.49 days for project A, 3.12 days for project  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Project** & **Baseline** & **MSRS** & **\% Delay** & **SMSRS** & **\% Delay** \\ \hline A & 14 & 4 & 28.57 & 5.49 & 39.21 \\ B & 32 & 3 & 9.38 & 6.12 & 19.13 \\ C & 70 & 8 & 11.43 & 15.77 & 22.53 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Percentage delay.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Project**} & \multicolumn{4}{c}{**Project Duration (Day)**} \\ \cline{2-5}  & **Baseline** & **SSRS** & **MSRS** & **SMSRS** \\ \hline A & 14 & 20 & 18 & 19.49 \\ B & 32 & 49 & 35 & 38.12 \\ C & 70 & 120 & 78 & 85.77 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Schedule summary.  
Figure 5: Percentage delay error.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Project** & **Baseline** & **MSRS** & **\% Delay** & **SMSRS** & **\% Delay** \\ \hline A & 14 & 4 & 28.57 & 5.49 & 39.21 \\ B & 32 & 3 & 9.38 & 6.12 & 19.13 \\ C & 70 & 8 & 11.43 & 15.77 & 22.53 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Percentage delay.  
B and 7.77 days for project C were observed revealing the extent of underestimation (uncertainty) of the existing MSRS model. These values indicate the impact of risk and uncertainty on the existing MSRS model. The impact can be higher depending on project type and size.  
Likewise, in Table 10, we compared the results of percentage delays (deviations) obtained from both the MSRS and SMRS models with the schedule baseline. For MSRS, the percentage delay for projects A, B, and C is 28.57%, 9.38%, and 11.43%, respectively. These values indicate the amount of deviation of the project baseline schedule considering risk and uncertainty associated with activity duration and resource constraint. As for SMSRS, the percentage delay is 39.21% for project A, 19.13% for project B, and 22.53% for project C indicating the amount of deviation of project baseline from the SMSRS based on stochastic activity duration. Note that the values obtained from the SMSRS model are the expected percentage delay for each project taken into account risk and uncertainty. Figure 5 shows the percentage delay error for the projects. Project A is 10.64%, while projects B and C are 9.75% and 11.10%, respectively. The average percentage error for all three projects is 10.50%. This value points out the error in the estimation of project delay using the existing MSRS model. Therefore, based on these results the proposed SMSRS model offers a more realistic resource schedule with a minimized expected delay.