Logistics Distribution Process Design Based on Stochastic Petri Nets and Big Data Algorithms

Abstract

-Logistics is to distribute goods to corresponding transportation routes according to the demand of goods through warehouse operation, so as to meet customer demand and arrive at the destination on time. The distribution process is the core of the entire logistics system, and its operation speed is directly related to the efficiency of the entire logistics system. In order to improve the distribution efficiency and reduce the transit time, it is necessary to optimize the design of the logistics distribution process. However, the current distribution process is characterized by high cost, low efficiency, and low degree of informatization and labeling, which in turn affects customer satisfaction and enterprise interests. Therefore, aiming at these problems, this paper designs a logistics distribution process based on stochastic Petri net and big data algorithm. Through stochastic Petri net modeling, the distribution process is quantitatively analyzed, the distribution business process model is established and optimized, and the modeling method based on stochastic Petri net is successfully applied to the logistics distribution business process to achieve efficient and low-cost logistics distribution.