Design of logistics center location method based on supply chain big data

For the location selection of logistics centers, there has always been an inaccurate analysis of supply chain data, resulting in low location accuracy. This paper proposes a logistics center location method based on supply chain big data. First, the Euclidean distance is used to calculate the similarity of the supply chain data. Secondly, the supply chain data is predicted through the Markov chain. Based on this, the objective function of the location of the logistics center can be established by combining the inertia weight. Clustering is carried out to determine the location of the logistics center, and finally the experimental analysis is carried out. The experimental results show that the improved method has high traffic convenience and can effectively improve the location accuracy of the logistics center.