Research On The Optimization Of Fresh Produce Distribution Path For Community Group Purchase

In today’s society,technological advances have driven the booming development of ecommerce,with new retail community group-buying models such as Meituan Yousei and Duo Duo Buying rapidly emerging to bring a more convenient shopping experience to community residents.The popularity of fresh e-commerce produce with high cost performance has increased significantly.At the same time,consumers are also paying more and more attention to the quality of the products and the shopping experience,and community group-buying platforms are demanding more from the delivery of goods.Therefore,optimising logistics and distribution services has become an important factor for community group-buying companies to consider.Community group buying fresh produce end delivery is a short distance cold chain transport,community group buying enterprises need to ensure the quality of fresh produce while meeting the customer’s requirements for delivery time.Therefore,scientific and effective planning of distribution paths can not only reduce distribution costs and quality change rate of fresh produce,but also improve customer satisfaction,which is of certain practical significance to community group-buying enterprises.In this paper,through the analysis and research of theories related to community group purchase mode,fresh produce distribution and vehicle path optimisation,as well as the research on the distribution situation of community group purchase of Company D,a community group purchase fresh produce distribution path optimisation model was established.The model takes the total cost of fresh produce distribution as the objective function,and the total cost includes vehicle fixed cost,vehicle driving cost,cargo damage cost,refrigeration cost,penalty cost and carbon emission cost.In view of the large number of parameters involved in the model and the large scale of the data,this paper chooses to use a genetic algorithm to solve the model,and uses a variable neighbourhood improvement genetic algorithm.Finally,the model and algorithm were solved in MATLAB environment for the case of fresh produce delivery in community group purchase of company D.The results showed that compared with the traditional genetic algorithm solved with the improved genetic algorithm,the vehicle driving cost was reduced by 9.56%,the cargo loss cost was reduced by 26.42%,the carbon emission cost was reduced by 9.59%,the time window penalty cost was reduced by 82.52%,and the total cost was reduced by 11.57%.The total cost is reduced by 11.57%and the algorithm converges faster and more consistently.The feasibility of the model and algorithm designed in this paper is confirmed,as well as the practicality of the research.The model and algorithm designed in this paper have been proved to be feasible and practical.It is of certain guidance and reference significance for enterprises to carry out community group purchase fresh produce delivery path optimisation.