# Urban Transportation Network Design for Fresh Fruit and Vegetables Using GIS-The Case of Bangkok
## 6 Conclusions  
A cold chain for perishable foods aims to maintain the food safety and quality of the products under temperature monitoring and control. Transportation and distribution within delivery time  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Demand** & **120\%** & **150\%** & **200\%** & **120\%** & **150\%** & **200\%** \\ \cline{2-7}
**Increases/Scenario** & \multicolumn{4}{c}{**Number of Required Trucks**} & \multicolumn{4}{c}{**\% Change when Compared with Current Demand**} \\ \hline  
windows become a challenge for the fresh food management. With urban population growth and increasing traffic congestion issues, a major existing DC may inefficiently meet customer requirements. To support the increasing demand and improve the quality of life in Bangkok metropolitan, an advanced transportation and distribution network for fresh products is needed. This research aimed to design a transportation network for fresh fruit and vegetables considering total travel time, total travel distance, and fairness among drivers by integrating LAP and VRPTW analysis. In addition, the results of LRP were obtained based on the actual location of origin, destination, and candidate DCs. Furthermore, candidate DCs were selected by minimizing facility location and maximizing coverage approach. All possible scenarios were devised and compared in terms of their performance based on six quantitative indicators: the number of the DCs, total travel distance, total travel time, the standard deviation of travel distance, and travel time, which refers to fairness among drivers, as well as the number of required trucks. The results highlight that the alternative scenarios based on mathematical models can guarantee a significantly improved performance, such as total travel time, total travel distance, and fairness than the current distribution network. For instance, when considering total travel time and distance from wholesaler to retailer via DCs, scenario 8 with seven DCs showed the best performance in travel time, while scenario 6 with five DCs showed the shortest distance. In terms of fairness, scenario 7 with six DCs may be regarded as the best alternative with the highest fairness indicator among drivers in both traveling time and distance. In addition, the results of performance evaluation may help the network designer consider and select a better scenario. Comparing makes it possible to enhance and balance economic, environmental, and social values to achieve sustainability in urban distribution. In order to consider the balance of the assigned workload in this research, we designed the fairness indicator based on the standard deviation of traveling distance and time across drivers. There are several methods to extend this research that can be suggested as future research directions. First, in order to make the problem simple without a loss of generalizability of our results, we did not specify the capacity of each DC at the beginning of the study. However, it may be helpful to design and develop a flexible transportation network. Second, it is difficult to forecast the demand for fresh fruit and vegetables from each retailer in Bangkok city. The demand for fresh fruit and vegetables was calculated based on the average consumption per year and the population of each district in Bangkok. The current results may be improved by securing the category and practical demand for fresh products from the retailer. Third, we have applied to the fixed average speed of outside and inside of the Bangkok area for solving VRPTW. However, the speed of trucks will be different according to the traffic status. Therefore, after securing the actual average speed of all roads, it is possible to elaborate the result of this research. Fourth, there is not enough information and data about land price, construction cost, and operating cost in fresh food DC. Therefore, the investment cost and operating cost should be calculated in future research.