MPC Control and Simulation of a Mixed Recovery Dual Channel Closed-Loop Supply Chain with Lead Time

Haifeng Guo, Bai Li
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Abstract

With the emergence of e-commerce, the closed-loop supply chain composed of e-commerce direct sale channel and reverse logistics formed by return and exchange is becoming more and more complex. The lead time of each node in the supply chain increases the uncertainty of the system, making it more difficult to restrain bullwhip effect. The model predictive control (MPC) method is used to restrain the bullwhip effect. Firstly, based on the state-space model of the mixed recovery dual-channel closed-loop supply chain with lead time, an augmented state-space model is established through state reorganization to solve network complexity caused by the lead time; Secondly, a structural diagram is constructed in the SIMULINK environment. The prediction model, the state estimation, and the objective function are presented. Thirdly, the KWIK quadratic programming method is derived, and the solution steps of the method are given. Finally, by simulating with random demand and sinusoidal demand as system input, the effectiveness of the method is verified. The results show that this method can effectively restrain the bullwhip effect and make the production, ordering and inventory curves tend to be smooth.
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带提前期的混合回收双通道闭环供应链的MPC控制与仿真
随着电子商务的出现,由电子商务直销渠道和退货交换形成的逆向物流组成的闭环供应链变得越来越复杂。供应链中各节点的提前期增加了系统的不确定性,使得牛鞭效应更难抑制。采用模型预测控制(MPC)方法抑制牛鞭效应。首先,在考虑提前期的混合回收双通道闭环供应链状态空间模型的基础上,通过状态重组建立了增强状态空间模型,解决了提前期引起的网络复杂性问题;其次,在SIMULINK环境下构造了结构框图。给出了预测模型、状态估计和目标函数。第三,导出了KWIK二次规划方法,并给出了该方法的求解步骤。最后,通过随机需求和正弦需求作为系统输入的仿真,验证了该方法的有效性。结果表明,该方法能有效地抑制牛鞭效应,使生产、订货和库存曲线趋于平滑。
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