Research On The Route Optimization Of Cold Chain Logistics Distribution Based On Internet Of Vehicles

In the Cold chain logistics distribution, consumers are mainly concerned about logistics timeliness and product quality, while the carriers of cold chain logistics attach more importance to the logistics cost. Therefore, taking into account of logistics timeliness and cost is a hot issue in the field of cold chain logistics distribution. The research on Cold chain logistics distribution mainly aim at the vehicle routing problem. Normally the VRP is to make the road speed as a fixed value, designed to achieve a lowest cost and plan out a best route. But in the actual situation, the road speed in the process of logistics distribution is dynamical, simply put it as a fixed value will not only make the final distribution plan deviate from the actual situation, but also will greatly reduce the research value.This paper discusses the characteristics of cold chain logistics and Internet of Vehicles, analyzes the feasibility and advantages of the combination of Internet of Vehicles and cold chain logistics distribution. Under the Internet of Vehicles platform, through handling the road traffic information which acquired from the Internet of Vehicles, we can get the road average-speeds between each of the customer. Based on the traditional vehicle routing optimization model,built up the route optimization model of cold chain logistics distribution based on the Internet of Vehicles, this model can not only make the sum of the transport cost, cooling costs, damage cost and time penalty cost to the minimum, but also can take into account the distribution timeliness. As this model process the road speed data, it can simulate the actual situation in a certain extent. Then a case with a small-scale data are used to test the validity of the model by the LINGO software. On the basis of proving the model correct, the improved genetic algorithm is used to solve the same case to prove the correctness and efficiency. At last, the algorithm is used to solve the actual distribution problem. By comparing the existing distribution costs and the distribution costs of using the improved genetic algorithm, it prove that the model is effective and practical.