A Bullwhip Effect Weakening Approach Based on VMD-SVM Algorithm under the Background of Intelligent Manufacturing

Processes

Li Shi¹  Xiangzhi Zhuo²  Minghao Zhang²  Yuan Liu² 

[1] College of Computer Science and Technology, Huaibei Normal University, Huaibei 235000, China;College of Economics and Management, Huaibei Normal University, Huaibei 235000, China;

关键词: intelligent manufacturing;    bullwhip effect;    demand forecasting;    variational mode decomposition;    support vector machine;   

DOI  :  10.3390/pr9111957

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown