# Urban Transportation Network Design for Fresh Fruit and Vegetables Using GIS-The Case of Bangkok
## 5 Result and Discussion
### Comparison of the Resources and Required Capacity of DC  
In order to build a new facility, it is necessary to consider the project and budget planning. To determine the number of DC, the number of required trucks, and the capacity of DC, all factors were related to the budget. Therefore, we examined two aspects to find insights for investment. First, we compared the number of DCs and the number of trucks to explore the relationship when the number of DC is changed. Second, through a comparison among the capacity of selected DCs, we were able to analyze the balancing capacity for each scenario. The result of the LRP analysis concerning the number of DCs and the number of required trucks is reported in Figure 9. Scenario 1, with only one current DC, showed the highest performance in terms of the number of trucks (70). Even though scenario 8 required the biggest number of DCs (7 DC), it required only 73 trucks, which is similar to the minimum value, 70. Therefore, it can be concluded that scenario 8 did not require more trucks, even though the number of DC is increased. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Scenario**} & \multirow{2}{*}{\begin{tabular}{c} **Number of** \\ **Selected** \\ **DCs** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Max. Lead** \\ **Time (min)** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Number of** \\ **Required** \\ **Tucks** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Travel Time (h)** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **Travel Distance** \\ **(km)** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Improvement** \\ **Compared with** \\ **Scenario 1 (\%)** \\ \end{tabular} } \\ \cline{4-9}  & & & & & **Total** & **STDEV** & **Total** & **STDEV** & **Time** & **Distance** \\ \hline Scenario 1 & 1 & - & 70 & 632.05 & 2.12 & 3927.40 & 13.25 & - & - \\ Scenario 2 & 8 & - & 72 & 188.77 & 0.91 & 1172.98 & 5.62 & 70.13 & 70.96 \\ Scenario 3 & 2 & 180 & 70 & 231.60 & 1.07 & 1439.07 & 6.64 & 63.36 & 63.36 \\ Scenario 4 & 3 & 180 & 71 & 214.02 & 1.11 & 1329.86 & 6.88 & 66.14 & 66.62 \\ Scenario 5 & 4 & 180 & 71 & 195.13 & 1.09 & 1212.46 & 6.78 & 69.13 & 69.56 \\ Scenario 6 & 5 & 180 & 71 & 185.23 & 0.93 & 1150.98 & 5.78 & 70.69 & 71.11 \\ Scenario 7 & 6 & 180 & 72 & 178.86 & 0.88 & 1111.38 & 5.45 & 71.70 & 72.49 \\ Scenario 8 & 7 & 180 & 73 & 178.50 & 0.90 & 1109.12 & 5.60 & 71.76 & 72.92 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Summary of the results of the VRPTW analysis. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scenario** & **Number of DC** & **Analysis Method** & **Selected DCs** \\ \hline Scenario 1 & 1 & - & Existing DC \\ Scenario 2 & 8 & Closest Facility & 1, 2, 4, 5, 6, 7 and 8 \\ Scenario 3 & 2 & Minimize facilities & 2 and 6 \\ Scenario 4 & 3 & Maximize coverage & 2, 7 and 8 \\ Scenario 5 & 4 & Maximize coverage & 1, 2, 6 and 7 \\ Scenario 6 & 5 & Maximize coverage & 1, 2, 4, 6 and 7 \\ Scenario 7 & 6 & Maximize coverage & 1, 2, 4, 6, 7 and 8 \\ Scenario 8 & 7 & Maximize coverage & 1, 2, 4, 5, 6, 7 and 8 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Summary of the results of the LAP analysis. According to the results of VRPTW, all 141 retailers were covered by the number of trucks. Most drivers can supply only two retailers for a trip, as the capacity of the truck was limited. This is the main reason why the number of trucks for each scenario ranged from about 70 to 73. Therefore, the budget for the vehicle is quite similar for each scenario, so the budget for the building DCs was totally different based on the number of DC. Figure 10 shows the required capacity of the selected DCs for each scenario. According to the assumption, all demand for retailers was allocated to the selected DCs. Therefore, the sum of the required capacity of the selected DCs was equal to the total demand.