# Urban Transportation Network Design for Fresh Fruit and Vegetables Using GIS-The Case of Bangkok
## 2 Literature Review  
The LRP is one of the major problems in designing a logistics network, with important implications for the entire supply chain [12]. There are several distinctive characteristics of the fresh products transportation that should be accounted for in solving the LRP. These characteristics include shelf life constraints and perishability of products, long production throughput time, seasonality in production, conditioned transportation and storage, product safety issues, and natural conditions that affect the quantity and quality of farm products [4; 13]. Generally, the fresh chain logistics builds customer value by merging logistics activities related to perishable products with common business processes [14; 15]. In one relevant study, [PERSON], [PERSON], and [PERSON] [3] modeled and resolved a cold chain distribution planning problem for perishable foods by generating a distribution plan that ensured the fulfillment of customer requirements for various foods and food quality levels at the lowest cost. Furthermore, [PERSON], [PERSON], [PERSON], and [PERSON] [16] designed the sustainable cold chain for food distribution on the silk road belt. A mixed integer linear programming model was applied to minimize the total energy consumption deal with the cold chain operation. The case study focused on the distribution for the perishable product along the new Silk Road, Europe, and China. The results suggested an efficient route and transportation modes on the sustainability of the cold chain. Similarly, [PERSON], [PERSON], [PERSON], and [PERSON] [17] evaluated the performance of an integrated food distribution network (IFDN) in Sweden. LRP analysis was applied to analyze the data of 11 producers, 149 customers, and one DC. GIS tools and LAP techniques were used. Four scenarios of food distribution were identified and analyzed. The number of routes, visits, transport distance, and total time were compared. [PERSON], [PERSON], and [PERSON] [18] integrated the LRP model and a hybrid heuristic solution methodology to solve the competitive multi-facility location problem. A GIS-based framework was used to store, analyze, and visualize all data, as well as to propose model solutions in the geographic project. Furthermore, [PERSON], [PERSON], [PERSON], and [PERSON] [19] considered four different scenarios to investigate the existing flow of locally produced foods from producers to consumers in Sweden. In addition, a coordinated and efficient food distribution system for local food producers was developed. GIS and Route Logix software (version, Manufacturer, City, US State abbrev. if applicable, Country) were used to get more insight into the impact of the integration of local food systems. In another relevant study, [PERSON], [PERSON], [PERSON], and [PERSON] [20] investigated the problem of last-mile delivery of fresh fruits and vegetables through considering multiple practical scenarios. A last-mile routing with the quality concern for cold-chain delivery was considered. The results indicated that the fulfillment of various requirements of different customers and appropriate quality levels could be ensured using cost considerations. In addition, [PERSON] and [PERSON] [21] proposed a model of facilities planning for a multi-temperature joint distribution system. The problem of optimal application of multi-temperature logistics techniques for terminal and vehicle routing operations was solved by minimizing the total delivery cost. This study focused on the choice of appropriate short-and medium-term operational strategies. In addition, the authors analyzed the advantages and disadvantages of various logistic techniques to provide operators with a valuable reference. Furthermore, [PERSON] and [PERSON] [2] proposed two types of decisions models: stopping transportation and/or rerouting the shipments to a closer location. The decision-making related to every shipment or series of shipments was made in the cloud using temporary virtual machines (VMs).