# A Study of an EOQ Model of Growing Items with Parabolic Dense Fuzzy Lock Demand Rate
## 7 Graphical Illustration  
In this section, we provide several graphs (Figures 9-13) to illustrate the numerical results in Table 2 and the sensitivity analysis results in Table 3. The figures are given below. Figure 9 shows that the inventory cost obtains the minimum value in a PDFLS environment, whereas it obtains the maximum in a crisp sense. Moreover, the inventory cost for the general fuzzy approach assumes a lower value than the parabolic dense fuzzy approach. Thus, by applying the parabolic dense fuzzy lock set approach, the inventory practitioner can minimize the total inventory cost. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameter** & **\% Change** & **Time (\(t_{2}^{*}\))** & **Time (\(t_{3}^{*}\))** & **Ordered Items (\(y^{*}\))** & **Total Cost (\(Z^{*}\))** & \(\frac{Z^{*}-Z_{\text{core}}}{Z_{\text{coip}}}\times\mathbf{100}\) \\ \hline \multirow{3}{*}{\(f\)} & \(+30\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(389,485.0\) & \(+21.91\) \\  & \(+10\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(330,012.8\) & \(+3.29\) \\  & \(-10\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(270,540.7\) & \(-15.31\) \\  & \(-30\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(211,068.6\) & \(-33.93\) \\ \hline \multirow{3}{*}{\(c_{2}\)} & \(+30\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,306.8\) & \(-6.00\) \\  & \(+10\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,286.3\) & \(-6.00\) \\  & \(-10\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,266.8\) & \(-6.01\) \\  & \(-30\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,246.8\) & \(-6.01\) \\ \hline \multirow{3}{*}{\(n_{c}\)} & \(+30\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,283.6\) & \(-6.00\) \\  & \(+10\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,279.0\) & \(-6.00\) \\  & \(-10\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,274.5\) & \(-6.01\) \\  & \(-30\) & \(0.5479\) & \(0.4330\) & \(2713\) & \(300,270.0\) & \(-6.01\) \\ \hline \multirow{3}{*}{\(\rho\)} & \(+30\) & \(0.5479\) & \(0.4330\) & \(2451\) & \(271,280.7\) & \(-15.08\) \\  & \(+10\) & \(0.5479\) & \(0.4330\) & \(2626\) & \(290,611.4\) & \(-9.03\) \\  & \(-10\) & \(0.5479\) & \(0.4330\) & \(2800\) & \(309,942.1\) & \(-2.98\) \\  & \(-30\) & \(0.5479\) & \(0.4330\) & \(2975\) & \(329,272.8\) & \(+3.06\) \\ \hline \multirow{3}{*}{\(\sigma\)} & \(+30\) & \(0.5479\) & \(0.4330\) & \(2923\) & \(323,512.8\) & \(+1.26\) \\  & \(+10\) & \(0.5479\) & \(0.4330\) & \(2783\) & \(308,022.1\) & \(-3.58\) \\ \cline{1-1}  & \(-10\) & \(0.5479\) & \(0.4330\) & \(2643\) & \(292,531.4\) & \(-8.43\) \\ \cline{1-1}  & \(-30\) & \(0.5479\) & \(0.4330\) & \(2503\) & \(277,040.7\) & \(-13.28\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._  
Figure 9: Inventory cost vs. methodology. Figure 10 shows that the approximated weight of fingerlings \((v_{0})\) and deviation parameter \((\rho,\,\sigma)\) were not very sensitive, whereas the price of fingerlings \((s)\), holding cost \((c_{2})\), and natural idle cost \((n_{c})\) were insensitive within this variation. However, the feeding cost \((f)\) and approximated weight of fish at the time of selling \((v_{1})\) were highly sensitive parameters for this system. Thus, to minimize the inventory cost, these two parameters \((f,v_{1})\) should be handled carefully. Figure 11 shows how the total inventory cost depends on time \(t_{1}\) and time \(t_{2}\). From this surface figure, it is clear that, when feeding time \(t_{1}\) increases and selling period \(t_{2}\) decreases, the inventory cost obtains the minimum value. Moreover, when feeding time \(t_{1}\) decreases and selling period \(t_{2}\) increases, the inventory cost decreases. On the other hand, when both \((t_{1},\,t_{2})\) increase or decrease together, the inventory cost also increases. Figure 11: Total inventory cost vs. time \(t_{1}\) and time \(t_{2}\). Figure 10: Sensitivity analysis of parameters. Figure 12 represents the relationship among ordered items, feeding time (\(t_{1}\)), and selling period (\(t_{2}\)).