Application of K-means Clustering Algorithms in Optimizing Logistics Distribution Routes

With the development of information technology and the arrival of the era of big data, China's logistics industry has been developing rapidly, especially in modern logistics management information system, In order to make full use of all kinds of resources and reduce logistics cost, this project extensively applies various information technologies related to mechanical learning. Taking the logistics distribution system of YifengWeiye Group as the research object, this paper puts forward the theory of K-means clustering algorithm and mileage-saving algorithm, adopts the idea of spatial clustering analysis regionalization, applies Python technology to process the special attribute data of transportation contained in the process of logistics distribution, and applies entity recognition technology based on attribute value partitioning algorithm and K-means clustering algorithm to realize the data area.