## 3 Proposed Methodology
### Hybrid Multi-Criteria Decision Analysis (MCDA)  
As discussed in Section 2.2, MCDA methods can enhance the decision-making processing thanks to their distinct features. While individual MCDA methods demonstrate strong performance when applied independently, the development of a hybrid MCDA algorithm that integrates multiple results of MCDA methods simultaneously presents a more comprehensive and efficient approach. Such a method can address the limitations of individual MCDA tools while leveraging their respective strengths, thereby providing a more robust solution. Accordingly, in this paper, a hybrid MCDA framework is used, which combines six widely-used methods, including VIKOR, COPRAS, CODAS, SAW, PROMETHEE, and TOPSIS, to extract a more robust outcome.  
The proposed approach offers a robust framework for analyzing complex projects involving multiple alternatives with overlapping features and key differences. It is particularly practical for selecting the best option in challenging scenarios where uncertainties and unresolved questions may hinder optimal decision-making. Finally, while applying each method individually may yield varying results due to differences in concepts and attributes, their combination addresses the limitations of individual methods and delivers more comprehensive and reliable outcomes.  
Additionally, there was an attempt to introduce a system implementation that facilitates straightforward and accessible weight computations for any decision matrix and the capability to compare outcomes obtained through different weighting methodologies, introduced as a hybrid MCDA. Numerous studies have also investigated the integration or  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Importance Level** & **Sub-Criteria Importance** & **Overall Importance** \\ \hline Aesthetics and Innovation & 16.10 & 3.83\% \\ Construction type & 19.40 & 4.61\% \\ Construction duration & 21.10 & 5.01\% \\ Design and Complexity & 23.30 & 5.54\% \\ Material selection & 20.10 & 4.77\% \\ Sum & 100.00 & 23.75\% \\ \hline \hline \end{tabular}
\end{table}
Table 7: Overall importance of ‘Engineering Design and Construction’ sub-criteria.  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Importance Level** & **Sub-Criteria Importance** & **Overall Importance** \\ \hline Procurement and Contract type & 19.60 & 4.83\% \\ Effective communication & 21.00 & 5.18\% \\ and Teamwork & 18.50 & 4.56\% \\ Legal and Political changes & 21.70 & 5.36\% \\ Supply chain & 19.20 & 4.73\% \\ Site maneuverability & 100.00 & 24.67\% \\ Sum & \\ \hline \hline \end{tabular}
\end{table}
Table 8: Overall importance calculation of ‘Logistics’ sub-criteria.  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Importance Level** & **Sub-Criteria Importance** & **Overall Importance** \\ \hline Operation and Maintenance cost & 19.70 & 5.22\% \\ Profitability & 20.10 & 5.35\% \\ Project duration and Scheduling & 20.10 & 5.34\% \\ Quality & 19.90 & 5.28\% \\ Productivity and efficiency & 20.10 & 5.34\% \\ Sum & 100.00 & 26.54\% \\ \hline \hline \end{tabular}
\end{table}
Table 9: Overall importance calculation of ‘Project Management’ sub-criteria.  
hybridization of two or more MCDA methods in diverse case studies. These endeavors aim to manage conflicting criteria and determine the optimal alternative solution [8].  
In order to integrate multiple MCDA methods into a unified decision-making framework, the Borda Count method is employed to combine the results. The computation details are explained in the next Section.