Abstract
In view of the current situation that the maturity of enterprise intelligent manufacturing capability is generally low and the information asymmetry in the upstream and downstream of the supply chain is high, taking any supply and demand link in the supply chain as an example, a group of initial demand signals that change nonlinearly over time are divided into intrinsic mode functions and noise residuals with different data characteristics by means of the variational modal decomposition (VMD) algorithm. On the basis of signal denoising and reconstruction, the support vector machine (SVM) algorithm is used to make regression prediction of the reconstructed signal with each intrinsic mode function as sample attribute. Compared with the regression prediction results of the original demand signal, it is verified that the VMD-SVM bullwhip effect weakening model can effectively filter the demand noise generated by each link in the supply chain and improve the accuracy of demand information transmission. It has a certain reference value to the weakening of the bullwhip effect and the improvement of supply chain synergy efficiency.
Highlights
In order to better serve demand forecasting, this paper extends the variational modal decomposition (VMD) algorithm with signal noise reduction function in the field of supply chain
This paper proposes to apply the VMD-support vector machine (SVM) algorithm to the weakening of the bullwhip effect
The method of demand forecasting has a strong correlation with the accuracy of final forecasting
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. From the achievements of China and Germany in intelligent manufacturing, the maturity of intelligent manufacturing capability at home and abroad is generally at a relatively basic level, which is reflected in that enterprises have a certain information foundation and can realize cross equipment and cross system data sharing, but they still cannot effectively eliminate cross enterprise information asymmetry In this case, how to use the existing technical means to improve the collaborative efficiency of such enterprises has become an important problem to be solved in supply chain management. This study intends to build a bullwhip effect weakening model based on VMD-SVM algorithm, split, reduce noise, reorganize, train and predict the demand signals in a demand cycle, and explore new methods to alleviate the bullwhip effect and improve the collaborative efficiency of supply chain
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