Volume 58, Number 1, January-February 2024
|303 - 326
|08 February 2024
Research on inventory replenishment strategy of supply chain based on SPN
School of business administration, Huaqiao University, Quanzhou 362021, P.R. China
2 College of Management and Economics, Tianjin University, Tianjin 300072, P.R. China
* Corresponding author: email@example.com
Accepted: 20 July 2023
The warehousing and replenishment strategy of supply chain is comprehensively affected by various factors such as supply chain structure, demand change, supply source, inventory state. Supply chain warehousing replenishment is full of uncertain factors, in order to achieve the optimal replenishment process and the best replenishment strategy effect, this paper uses SPN(Stochastic Petri net) to build the supply chain warehousing replenishment model. Based on the basis of the traditional replenishment process, this paper optimizes the new supply chain warehousing management process, optimizes the priority management measures of goods in the process of supply chain warehousing replenishment process, designs the new replenishment strategy algorithm and designs the replenishment strategy function analysis. Using SPN model, this paper intuitively shows the warehousing management process, and describes the dynamic changes of warehousing replenishment in detail. Through the implementation of different warehousing replenishment strategies to solve the influencing factors of uncertainty, so as to avoid the problem of various supply chain warehousing shortage caused by poor warehousing management. Finally, by comparing the traditional warehouse management strategy and the SPN model optimization of the supply chain storage strategy, the research result shows that the SPN replenishment strategy model is more efficient than the traditional warehouse replenishment strategy model.
Mathematics Subject Classification: 90B50 / 91A80
Key words: Supply chain / warehouse management / replenishment strategy / stochastic petri net (SPN)
© The authors. Published by EDP Sciences, ROADEF, SMAI 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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