## 4 Results
### Evaluation of Variables and Alternatives  
Using Equation (2), we calculated the highest possible fuzzy score for each of the factors. The crisp value was derived through the process of defuzzification, which involved applying Equation (3) to the fuzzy scores. The results are displayed in Table 7 and Figures 3 and 4. The criteria were ranked according to their fuzzy scores following a thorough analysis of every criterion. With the highest fuzzy score of one, the demand for freight occupies the top position and highlights its essential significance in decision-making. With a fuzzy score of, transportation expenditures come in second place, indicating the importance of taking them into account throughout the decision process. Third place comes from proximity to the customers, production region, and marketplace, recognizing the significance of geographic location and the high fuzzy score of. Seaports are always important for companies that depend on transport by sea, even with their high fuzzy score, which places them fourth among other factors with somewhat higher scores. With a fuzzy score of, highways rank fifth, suggesting that while they are important, they are not as important as other elements. With a fuzzy score of, inland waterways rank sixth and have a similar situation. The cost of purchasing land comes in at number seven, with a fuzzy score of, indicating that \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Criteria** & **Factor** & **Defuzzification** & **Fuzzy Score** & **Rank** \\ \hline
1 & Seaports & 0.79 & (0.63, 0.81, 0.93) & 4 \\
2 & Demand for freight & 0.87 & (0.74, 0.89, 0.97) & 1 \\  & Proximity to the & & & \\
3 & marketplace, & & & \\  & manufacturing region, & & & \\  & and customers & & & \\
4 & Highways & 0.68 & (0.49, 0.69, 0.85) & 5 \\
5 & Inland waterways & 0.67 & (0.49, 0.69, 0.84) & 6 \\  & The expense of & & & \\
6 & acquiring land & 0.66 & (0.49, 0.67, 0.83) & 7 \\
7 & Expense of constructing & 0.63 & (0.45, 0.63, 0.81) & 8 \\
8 & Railways & 0.57 & (0.38, 0.58, 0.76) & 9 \\
9 & Airports & 0.56 & (0.37, 0.57, 0.75) & 10 \\
10 & Transportation expenses & 0.86 & (0.74, 0.88, 0.95) & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Highest fuzzy criteria outcomes. Figure 3: Defuzzification values for factors. while expenses are considered, they are not as important. The construction cost comes in eighth place with a fuzzy score of, indicating that it is relevant but not a high priority. Railways rank ninth with a fuzzy score of, indicating that, while still important, they are not as important as higher-level criteria. Airports rank tenth and last among the factors mentioned, with the lowest fuzzy score of, suggesting their limited impact. This research highlights the importance of freight demand, transportation expenses, and proximity to the marketplace, manufacturing region, and customers in selecting a logistics center. To enhance freight transportation demand, economic growth policies and free trade zones are implemented. Transportation, land acquisition, and building costs are considered to reduce logistics expenses. LCs with combined logistics facilities and transport hubs prioritize proximity to water and highways for price and adaptability. Expanding geographical areas fosters sustainable development. The decision-making process assigns relatively lower priorities to building and transportation activities' environmental effects, as shown in Figures 5 and 6. The 10 determinants chosen for evaluating alternatives were linguistic variables that underwent a transformation process, resulting in fuzzy ratings. A \"weight-normalized fuzzy decision matrix,\" which was assessed by multiplying the ratings with the fuzzy weights, was calculated using Equation (6), and the positive ideal (\(A^{*}\)) and negative ideal (\(A^{-}\)) options under each factor were determined using Equations (7) and (8), as presented in Table 8 (Gwadar (GW), Ormara (OR), Qasim (QA), Pasni (PA), Gilgit (GI), Peshawar (PE), Quetta (QU), Karachi (KA), Tianjin (TI), and Khashgar (KH)).