Optimization of Warehousing Material Turnover Time Based on Clustering

Abstract

The warehousing and logistics industry is a basic, strategic and leading industry that supports the development of the national economy. Efforts must be made to improve the intelligent level of warehousing and logistics in the Turnover Time. Warehousing and logistics in the power field are large in scale and wide in scope. In this paper, we use exponential smoothing algorithm to compress large amounts of data while eliminating extreme data. K-means and DBSCAN algorithms are used to deal with data factors related to the turnover time of warehousing materials.