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Front. Inform. Technol. Electron. Eng.  2010, Vol. 11 Issue (5): 394-400    DOI: 10.1631/jzus.C0910270
    
Model predictive control with an on-line identification model of a supply chain unit
Jian Niu, Zu-hua Xu*, Jun Zhao, Zhi-jiang Shao, Ji-xin Qian
State Key Lab of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
Model predictive control with an on-line identification model of a supply chain unit
Jian Niu, Zu-hua Xu*, Jun Zhao, Zhi-jiang Shao, Ji-xin Qian
State Key Lab of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
 全文: PDF(154 KB)  
摘要： A model predictive controller was designed in this study for a single supply chain unit. A demand model was described using an autoregressive integrated moving average (ARIMA) model, one that is identified on-line to forecast the future demand. Feedback was used to modify the demand prediction, and profit was chosen as the control objective. To imitate reality, the purchase price was assumed to be a piecewise linear form, whereby the control objective became a nonlinear problem. In addition, a genetic algorithm was introduced to solve the problem. Constraints were put on the predictive inventory to control the inventory fluctuation, that is, the bullwhip effect was controllable. The model predictive control (MPC) method was compared with the order-up-to-level (OUL) method in simulations. The results revealed that using the MPC method can result in more profit and make the bullwhip effect controllable.
关键词： Supply chain;  Model predictive control;  On-line identification;  Optimization with constraint;  Piecewise linear price    
Abstract: A model predictive controller was designed in this study for a single supply chain unit. A demand model was described using an autoregressive integrated moving average (ARIMA) model, one that is identified on-line to forecast the future demand. Feedback was used to modify the demand prediction, and profit was chosen as the control objective. To imitate reality, the purchase price was assumed to be a piecewise linear form, whereby the control objective became a nonlinear problem. In addition, a genetic algorithm was introduced to solve the problem. Constraints were put on the predictive inventory to control the inventory fluctuation, that is, the bullwhip effect was controllable. The model predictive control (MPC) method was compared with the order-up-to-level (OUL) method in simulations. The results revealed that using the MPC method can result in more profit and make the bullwhip effect controllable.
Key words: Supply chain    Model predictive control    On-line identification    Optimization with constraint    Piecewise linear price
收稿日期: 2009-05-11 出版日期: 2010-04-28
CLC:  TP29  
基金资助: Project  supported  by  the  National  Natural  Science  Foundation of China (Nos. 60804023, 60934007, and 60974007), and the National
Basic Research Program (973) of China (No. 2009CB320603) 
通讯作者: Zu-hua XU     E-mail: xuzh@iipc.zju.edu.cn
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Jian Niu
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引用本文:

Jian Niu, Zu-hua Xu, Jun Zhao, Zhi-jiang Shao, Ji-xin Qian. Model predictive control with an on-line identification model of a supply chain unit. Front. Inform. Technol. Electron. Eng., 2010, 11(5): 394-400.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C0910270    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2010/V11/I5/394

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