Abstract
The optimal location of the hub of agricultural product transportation network is of great practical significance for improving the transportation efficiency and ensuring the freshness of agricultural products. The pure hierarchical hub-and-spoke transport network is used to model the agricultural products transportation, a genetic algorithm with two layers of chromosome coding is used to select the optimal hubs which ensure that all agricultural products are delivered on time and the total network cost is minimized. Moreover, sensitivity analysis was performed to explore the impact of the cost loss rate and delivery limit time on the location of hubs. Finally, the feasibility and advantages of our method were verified through the agricultural product transportation data of 48 states in the United States. The results shown that the total cost was reduced by 16.73% by compared with the direct routing transport. Through sensitivity analysis, it was found that when the cost loss rate decreased, the total transportation cost decreased, the number of hubs increased, and the ratio of hub cost to total transportation network cost increased. The experiments show that our model can effectively improve the efficiency of agricultural products transportation.
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