## 4 Bridge Case Study for CRP Assessment
### Bridge Case Study Results  
Following the completion of the decision-making matrix, the hybrid MCDA method with different MCDM methods, including TOPSIS, SAW, VIKOR, PROMETHEE, COPRAS, and CODAS was implemented based on their respective algorithms within the MATLAB R2024a software, as outlined in the research methodology.  
As a result, Figure 9 displays the outcomes of the hybrid MCDA analysis.  
Option 3 stands out with two scores of 1 in both PROMETHEE and COPRAS and then with four other close scores around 0.6 to 0.7 in TOPSIS, SAW, VIKOR, and COPRAS. In summary, it is evident that Option 3 did attain high rankings in the hybrid decision matrix values. Despite the comparisons and discussions, certain ambiguities persist in selecting the optimal choice.  
The Borda Count method is employed to conclude the best decision as the second approval. Despite the comparisons and the discussion, certain ambiguities persist in selecting the optimal choice; the Borda Count method is also utilized to assess the outcomes generated by various methods. Initially, rankings and their corresponding scores are taken into account. In this process, ranks ranging from 1 to 4 are assigned based on the highest to lowest results. Each rank is then associated with a score from 4 to 1, reflecting the highest score for the top result. The final score of each alternative will be obtained from the formula below, which means that the number of times each obtained rank in every alternative will be considered through all other previous methods.  
\begin{table}
\begin{tabular}{l l c c c c c} \hline \hline \multirow{2}{*}{**Main Groups**} & \multirow{2}{*}{**Criteria**} & \multicolumn{2}{c}{**Sub-Criteria**} & \multirow{2}{*}{**Option 1**} & \multirow{2}{*}{**Option 2**} & \multirow{2}{*}{**Option 3**} & \multirow{2}{*}{**Option 4**} \\  & & & & & & \\ \hline \multirow{4}{*}{Regulations} & Sustainability & 7.51\% & 6 & 4 & 3 & 8 \\  & Health and Safety & 9.99\% & 4 & 8 & 5 & 6 \\  & Urban Planning & 7.57\% & 9 & 6 & 4 & 4 \\  & Aesthetics and Innovation & 3.83\% & 9 & 6 & 8 & 3 \\  & Construction Type & 4.61\% & 9 & 9 & 9 & 5 \\  & Construction Duration & 5.01\% & 6 & 3 & 4 & 9 \\  & Design and Complexity & 5.54\% & 1 & 1 & 1 & 0.001 \\  & Material Selection & 4.77\% & 3 & 6 & 8 & 8 \\  & Operation and Maintenance Cost & 5.22\% & 4 & 2 & 7 & 5 \\  & Profitability & 5.35\% & 3 & 5 & 7 & 8 \\  & Project Duration and Scheduling & 5.34\% & 8 & 4 & 2 & 6 \\  & Quality & 5.28\% & 9 & 9 & 9 & 6 \\  & Productivity and Efficiency in & 5.34\% & 5 & 7 & 8 & 3 \\  & Resource Management & & 7.68\% & 6 & 8 & 9 & 3 \\  & Legal and Political Changes & 9.03\% & 4 & 5 & 7 & 9 \\  & Site Maneuverability & 7.96\% & 4 & 6 & 8 & 9 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Customized decision matrix.  
The results are illustrated with the final calculated score for each option in Figures 9 and 10; as it is seen, yet again, Option 3 attains the highest value, scoring 20, which not only serves as robust evidence supporting the analysis conducted in the preceding section--wherein we assumed Option 3 to be the top choice--but also confirms Option 2 is the closest positioned to Option 3 as the second choice.