# Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach
## 6 Sensitivity Analysis  
The sensitivity results depict how changing the weight of a particular criterion affects the ranking of the alternative machines A1, A2, A3, and A4. One-at-a-time sensitivity analysis was used to specify how the output of the decision model (in this study, alternative rankings) varied as each input parameter (in this study, criterion weight) was changed separately, keeping all other parameters fixed at their baseline values. This type of analysis helps to understand the sensitivity of the output to each parameter in isolation and pinpoints which parameters have the most powerful impact on the decision model's outcome.  
A sensitivity analysis involving 81 different scenarios was performed to determine the impact of each criterion's weight and \(\zeta\) level changes on the final scores and ranking results of the alternatives. In each scenario, the criterion's weight was increased from 0.1 to 0.9. While the weight of each criterion was changed, the weights of the remaining criteria were proportionally organized.  
Figure 2 illustrates the sensitivity results concerning criterion C1 (Speed). A1 was placed in the first rank until the weight of C1 was below 0.5. When the weight of C1 is below 0.4, A4 secures the second rank, followed by A2 in the third position. This stability demonstrates that alternative ranking does not change for low weights of C1, irrespective of \(\zeta\) changes. The alternative rankings fluctuate when the C1 weight is above 0.4. As the weight of C1 increases beyond 0.4 and \(\zeta\) is above 0.1, A2 surpasses A4, taking the second rank, while A4 falls to the third position. At a C1 weight of 0.6, the ranking changes once again, with A1 obtaining the second rank and A2 moving up to the first rank. This  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline \multirow{2}{*}{\(\zeta\)} & **A1** & \multicolumn{2}{c}{**A2**} & \multicolumn{2}{c}{**A3**} & \multicolumn{2}{c}{**A4**} \\ \cline{2-9}  & **Score** & **Ranking** & **Score** & **Ranking** & **Score** & **Ranking** & **Score** & **Ranking** \\ \hline
0.1 & 0.173 & 1 & \(-0.007\) & 2 & \(-0.126\) & 4 & \(-0.041\) & 3 \\
0.2 & 0.199 & 1 & 0.0003 & 2 & \(-0.14\) & 4 & \(-0.059\) & 3 \\
0.3 & 0.217 & 1 & 0.007 & 2 & \(-0.149\) & 4 & \(-0.075\) & 3 \\
0.4 & 0.237 & 1 & 0.009 & 2 & \(-0.162\) & 4 & \(-0.084\) & 3 \\
0.5 & 0.249 & 1 & 0.007 & 2 & \(-0.171\) & 4 & \(-0.084\) & 3 \\
0.6 & 0.237 & 1 & 0.009 & 2 & \(-0.162\) & 4 & \(-0.084\) & 3 \\
0.7 & 0.217 & 1 & 0.007 & 2 & \(-0.149\) & 4 & \(-0.075\) & 3 \\
0.8 & 0.199 & 1 & 0.0003 & 2 & \(-0.14\) & 4 & \(-0.059\) & 3 \\
0.9 & 0.173 & 1 & \(-0.007\) & 2 & \(-0.126\) & 4 & \(-0.041\) & 3 \\ \hline \hline \end{tabular}
\end{table}
Table 15: Alternative ranking.  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline  & **A1** & \multicolumn{2}{c}{**A2**} & \multicolumn{2}{c}{**A3**} & \multicolumn{2}{c}{**A4**} \\ \hline \(\zeta\) & **Euclidean** & **Taxicab** & **Euclidean** & **Taxicab** & **Euclidean** & **Taxicab** & **Euclidean** & **Taxicab** \\ \hline
0.1 & 0.095 & 0.069 & 0.064 & 0.058 & 0.043 & 0.046 & 0.061 & 0.046 \\
0.2 & 0.103 & 0.077 & 0.07 & 0.065 & 0.045 & 0.051 & 0.062 & 0.049 \\
0.3 & 0.11 & 0.082 & 0.076 & 0.068 & 0.048 & 0.053 & 0.063 & 0.051 \\variability points out that the importance of the Speed criterion is more decisive on A2 and A4 than that for A1 and A3. Their relative rankings are more susceptible to changes in the weight assigned to Speed.  
The sensitivity analysis results for the remaining criteria are given in Appendix A.