## 3 Proposed Method
For INSPs, seven levels have been considered, namely \"Extremely Low: EL\", \"Very Low: VL\", \"Low: L\", \"Moderate: M\", \"High: H\", \"Very High: VH\", and \"Extremely High: EH\". Later, the fuzzy rule base was developed, as shown in Table 5, reflecting each criterion's nature and selection possibilities (See Figure 5). Out of three parameters, INRE and INFBS are the benefit parameters, whereas INDE is the cost criterion. It may be noted that the weights of the selection possibilities should be considered for ranking the node possibilities, along with the relative importance of the selected attributes. Table 6 shows the decision matrix with 27 selection possibilities indicating fuzzy weights of the measures chosen and the node numbers. A fuzzy normalized decision matrix is shown in Table 7, which was developed using Equations (2) and (3). In addition, in this table, weights of the INSP are indicated, which were taken into account for developing the fuzzy weighted normalized decision matrix shown in Figure 2.1 This table considered weights of relative importance and weights of the selection possibilities, i.e., \(\
u_{\text{ij}}=\tau_{\text{ij}}\) *weight of the criteria (\(w_{i}\))*weight of the selection possibility (ws). Moreover, the FPIS and FNIS values are shown in Table 8, which were calculated using Equations (5) and (6). The distance of each node from the FPIS ( \(\left[\text{ }\left[\text{ d}\_{\text{i}}\right]\  
w\({}_{18}\) = 0.875025, w\({}_{3}\) = 0.744288, w\({}_{9}\) = 0.677472, and w\({}_{8}\) = 0.662365, respectively) are close to the positive ideal solution. On the other hand, node numbers 22, 20, 19, 10, and 1 are the least preferred numbers as their weights, i.e., w\({}_{22}\) = 0.087472, w\({}_{20}\) = 0.068519, w\({}_{19}\) = 0.05284, w\({}_{10}\) = 0.050204, and w\({}_{1}\) = 0.029671, respectively, are considerably distant from the FPIS. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**S. N**} & **INRE** & **INFBS** & **INDE** \\  & **(Benefit Criterion)** & **(Benefit Criterion)** & **(Cost Criterion)** & **INSP** \\ \hline
1 & L & S & N & VL \\ \hline
2 & L & A & N & Mo \\ \hline
3 & L & B & N & VH \\ \hline  
& S & Fa & VL \\ \hline
26 & H & A & Fa & Mo \\ \hline
27 & H & B & Fa & VH \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Decision matrix. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Weights (w\({}_{j}\))**} & **5.5** & **10** & **10** & **1** & **1** & **5** & **1** & **5.5** & **10** & & & \\ \hline
**S.N** & & **INRE** & & & **INFBS** & & & **INDE** & & **INSP (w\({}_{s}\))** & \\ \hline
1 & 0.1 & 0.1 & 0.55 & 0.1 & 0.1 & 0.55 & 0.1 & 0.1 & 0.1818 & 1 & 2 & 3 \\
2 & 0.1 & 0.1 & 0.55 & 0.1 & 0.55 & 1 & 0.1 & 0.1 & 0.1818 & 4 & 5.5 & 7 \\
3 & 0.1 & 0.1 & 0.55 & 0.55 & 1 & 1 & 0.1 & 0.1 & 0.1818 & 8 & 9 & 10 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Normalized Fuzzy decision matrix. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**Weights (w\({}_{j}\))** & **5.5** & **10** & **10** & **1** & **1** & **5** & **1** & **5.5** & **10** & & & \\ \hline
**S.N** & **INRE** & & & & & & & & & & & & \\ \hline  
55 & 0.1818 & 1 & 1 & 1 & 2 & 3 \\ \hline \hline \end{tabular}
\end{table}