Research on model predictive control for inventory management in decentralized supply chain system

Hai Dong; Xiao Hua Tang; Yan Tong; Yan Ping Li

doi:10.1109/ICIII.2009.67

Research on model predictive control for inventory management in decentralized supply chain system

Hai Dong^*
, Xiao Hua Tang
, Yan Tong
, Yan Ping Li

^*Corresponding author for this work

Shenyang University
Liaoning University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

In a decentralized supply chain system, it is very important to forecast the changes in the market in order to maintain an inventory level that is just enough to satisfy customer demand. A optimization-based control approach for supply chain networks is presented. The control strategy applies model predictive control principles to the entire supply chain networks, and supply chains whose dynamic behavior can be adequately represented by fluid analogies. A Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm is presented as a means to obtain optimal tuning parameters for the proposed policies. The SPSA technique is capable of optimizing important system parameters, such as safety stock targets and controller tuning parameters. Simulated results exhibit good dynamic performance and financial benefit under maintaining robust operation in a decentralized supply chain system.

Original language	English
Title of host publication	2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009
Pages	250-253
Number of pages	4
DOIs	https://doi.org/10.1109/ICIII.2009.67
Publication status	Published - 2009
Externally published	Yes
Event	2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009 - Xi'an, China Duration: 26 Dec 2009 → 27 Dec 2009

Publication series

Name	2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009
Volume	1

Conference

Conference	2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009
Country/Territory	China
City	Xi'an
Period	26/12/09 → 27/12/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Fluid analogy
Model predictive control
SPSA
Supply chain

Access to Document

10.1109/ICIII.2009.67

Cite this

Dong, H., Tang, X. H., Tong, Y., & Li, Y. P. (2009). Research on model predictive control for inventory management in decentralized supply chain system. In 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009 (pp. 250-253). Article 5369220 (2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009; Vol. 1). https://doi.org/10.1109/ICIII.2009.67

Dong, Hai ; Tang, Xiao Hua ; Tong, Yan et al. / Research on model predictive control for inventory management in decentralized supply chain system. 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009. 2009. pp. 250-253 (2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009).

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title = "Research on model predictive control for inventory management in decentralized supply chain system",

abstract = "In a decentralized supply chain system, it is very important to forecast the changes in the market in order to maintain an inventory level that is just enough to satisfy customer demand. A optimization-based control approach for supply chain networks is presented. The control strategy applies model predictive control principles to the entire supply chain networks, and supply chains whose dynamic behavior can be adequately represented by fluid analogies. A Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm is presented as a means to obtain optimal tuning parameters for the proposed policies. The SPSA technique is capable of optimizing important system parameters, such as safety stock targets and controller tuning parameters. Simulated results exhibit good dynamic performance and financial benefit under maintaining robust operation in a decentralized supply chain system.",

keywords = "Fluid analogy, Model predictive control, SPSA, Supply chain",

author = "Hai Dong and Tang, \{Xiao Hua\} and Yan Tong and Li, \{Yan Ping\}",

year = "2009",

doi = "10.1109/ICIII.2009.67",

language = "English",

isbn = "9780769538761",

series = "2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009",

pages = "250--253",

booktitle = "2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009",

note = "2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009 ; Conference date: 26-12-2009 Through 27-12-2009",

}

Dong, H, Tang, XH, Tong, Y & Li, YP 2009, Research on model predictive control for inventory management in decentralized supply chain system. in 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009., 5369220, 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009, vol. 1, pp. 250-253, 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009, Xi'an, China, 26/12/09. https://doi.org/10.1109/ICIII.2009.67

Research on model predictive control for inventory management in decentralized supply chain system. / Dong, Hai; Tang, Xiao Hua; Tong, Yan et al.
2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009. 2009. p. 250-253 5369220 (2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Tang, Xiao Hua

AU - Tong, Yan

AU - Li, Yan Ping

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N2 - In a decentralized supply chain system, it is very important to forecast the changes in the market in order to maintain an inventory level that is just enough to satisfy customer demand. A optimization-based control approach for supply chain networks is presented. The control strategy applies model predictive control principles to the entire supply chain networks, and supply chains whose dynamic behavior can be adequately represented by fluid analogies. A Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm is presented as a means to obtain optimal tuning parameters for the proposed policies. The SPSA technique is capable of optimizing important system parameters, such as safety stock targets and controller tuning parameters. Simulated results exhibit good dynamic performance and financial benefit under maintaining robust operation in a decentralized supply chain system.

AB - In a decentralized supply chain system, it is very important to forecast the changes in the market in order to maintain an inventory level that is just enough to satisfy customer demand. A optimization-based control approach for supply chain networks is presented. The control strategy applies model predictive control principles to the entire supply chain networks, and supply chains whose dynamic behavior can be adequately represented by fluid analogies. A Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm is presented as a means to obtain optimal tuning parameters for the proposed policies. The SPSA technique is capable of optimizing important system parameters, such as safety stock targets and controller tuning parameters. Simulated results exhibit good dynamic performance and financial benefit under maintaining robust operation in a decentralized supply chain system.

KW - Fluid analogy

KW - Model predictive control

KW - SPSA

KW - Supply chain

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U2 - 10.1109/ICIII.2009.67

DO - 10.1109/ICIII.2009.67

M3 - Conference contribution

AN - SCOPUS:77649311648

SN - 9780769538761

T3 - 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009

SP - 250

EP - 253

BT - 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009

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ER -

Dong H, Tang XH, Tong Y, Li YP. Research on model predictive control for inventory management in decentralized supply chain system. In 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009. 2009. p. 250-253. 5369220. (2009 International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2009). doi: 10.1109/ICIII.2009.67

Research on model predictive control for inventory management in decentralized supply chain system

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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