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A constrained EPSAC approach to inventory control for a benchmark supply chain system

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Abstract
The design of an appropriate inventory control policy for a supply chain (SC) plays an essential role in tempering inventory instability and bullwhip effect. Several constraints are commonly encountered in actual operations so managers are required to take these physical restrictions into account when designing the inventory control policy. Model predictive control (MPC) appears as a promising solution to this issue, due to its capability of finding optimal control actions for a constrained SC system. Therefore, the inventory control problem for a benchmark SC is solved using the extended prediction self-adaptive control approach to MPC. To extend methodologies in our previous work, the control framework relies on generic process model and incorporates the physical constraints arising from practical operations to form the general constrained optimisation problems. The managers can choose from decentralised and centralised control structures according to specific informational and organisational factors of their SCs. The proposed control schemes in this study may be appropriate for industrial practice because the designed policy can bring a reduction of over 30% in operating cost and a significant increase of customer satisfaction level compared with that of the conventional policy.
Keywords
CONTROL STRATEGY, MODEL-PREDICTIVE CONTROL, DECISION-MAKING, MANAGEMENT, OPTIMIZATION, POLICY, CONFIGURATION, ORDER, supply chain, model predictive control, inventory control, constrained control

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Citation

Please use this url to cite or link to this publication:

MLA
Fu, Dongfei et al. “A Constrained EPSAC Approach to Inventory Control for a Benchmark Supply Chain System.” INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 54.1 (2016): 232–250. Print.
APA
Fu, D., Ionescu, C.-M., Aghezzaf, E.-H., & De Keyser, R. (2016). A constrained EPSAC approach to inventory control for a benchmark supply chain system. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 54(1), 232–250.
Chicago author-date
Fu, Dongfei, Clara-Mihaela Ionescu, El-Houssaine Aghezzaf, and Robain De Keyser. 2016. “A Constrained EPSAC Approach to Inventory Control for a Benchmark Supply Chain System.” International Journal of Production Research 54 (1): 232–250.
Chicago author-date (all authors)
Fu, Dongfei, Clara-Mihaela Ionescu, El-Houssaine Aghezzaf, and Robain De Keyser. 2016. “A Constrained EPSAC Approach to Inventory Control for a Benchmark Supply Chain System.” International Journal of Production Research 54 (1): 232–250.
Vancouver
1.
Fu D, Ionescu C-M, Aghezzaf E-H, De Keyser R. A constrained EPSAC approach to inventory control for a benchmark supply chain system. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH. Taylor & Francis; 2016;54(1):232–50.
IEEE
[1]
D. Fu, C.-M. Ionescu, E.-H. Aghezzaf, and R. De Keyser, “A constrained EPSAC approach to inventory control for a benchmark supply chain system,” INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, vol. 54, no. 1, pp. 232–250, 2016.
@article{7034317,
  abstract     = {The design of an appropriate inventory control policy for a supply chain (SC) plays an essential role in tempering inventory instability and bullwhip effect. Several constraints are commonly encountered in actual operations so managers are required to take these physical restrictions into account when designing the inventory control policy. Model predictive control (MPC) appears as a promising solution to this issue, due to its capability of finding optimal control actions for a constrained SC system. Therefore, the inventory control problem for a benchmark SC is solved using the extended prediction self-adaptive control approach to MPC. To extend methodologies in our previous work, the control framework relies on generic process model and incorporates the physical constraints arising from practical operations to form the general constrained optimisation problems. The managers can choose from decentralised and centralised control structures according to specific informational and organisational factors of their SCs. The proposed control schemes in this study may be appropriate for industrial practice because the designed policy can bring a reduction of over 30% in operating cost and a significant increase of customer satisfaction level compared with that of the conventional policy.},
  author       = {Fu, Dongfei and Ionescu, Clara-Mihaela and Aghezzaf, El-Houssaine and De Keyser, Robain},
  issn         = {0020-7543},
  journal      = {INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH},
  keywords     = {CONTROL STRATEGY,MODEL-PREDICTIVE CONTROL,DECISION-MAKING,MANAGEMENT,OPTIMIZATION,POLICY,CONFIGURATION,ORDER,supply chain,model predictive control,inventory control,constrained control},
  language     = {eng},
  number       = {1},
  pages        = {232--250},
  publisher    = {Taylor & Francis},
  title        = {A constrained EPSAC approach to inventory control for a benchmark supply chain system},
  url          = {http://dx.doi.org/10.1080/00207543.2015.1070214},
  volume       = {54},
  year         = {2016},
}

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