Logistics scheduling method and system based on big data

Abstract

The invention discloses a logistics scheduling method and system based on big data, and belongs to the technical field of logistics scheduling, and the method comprises the steps: obtaining order data, vehicle data and environment data based on monitoring equipment and a transaction system; preprocessing the order data, the vehicle data and the environment data to obtain a preprocessed data set; constructing a decision tree machine learning model, optimizing the decision tree machine learning model, and training the optimized decision tree machine learning model based on the sample set to obtain a logistics scheduling model; and inputting the preprocessed data set into the logistics scheduling model for calculation, generating a scheduling result, and scheduling logistics based on the scheduling result. The decision tree model can quickly generate decision rules according to a large amount of historical data and real-time data. The rules can accurately guide decisions in the logistics scheduling process, such as route planning, vehicle distribution and the like.

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