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Inventory control for the supply chain: An adaptive control approach based on the identification of the lead-time

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  • Garcia, C.A.
  • Ibeas, A.
  • Herrera, J.
  • Vilanova, R.

Abstract

In this paper, an Internal Model Control (IMC) scheme is incorporated in production inventory control systems in a complete supply chain. This control scheme presents a good target inventory tracking under the perfect knowledge of the system. Furthermore, the inventory tracking and load disturbance rejection control problems can be tackled separately. However, the closed-loop performance of the IMC scheme may be degraded due to a mismatch between the modelled and actual delay or to the fact that delays may be time-varying. Thus, the IMC control scheme is enhanced in this work with a novel method for the online identification of lead times based on a multimodel scheme. In this way, all benefits of the IMC scheme can be exploited. A detailed discussion of the proposed production inventory system is provided including a stability and performance analysis as well as the identification capabilities of the algorithm. Several simulation examples illustrate the efficiency of the approach.

Suggested Citation

  • Garcia, C.A. & Ibeas, A. & Herrera, J. & Vilanova, R., 2012. "Inventory control for the supply chain: An adaptive control approach based on the identification of the lead-time," Omega, Elsevier, vol. 40(3), pages 314-327.
    • Handle: RePEc:eee:jomega:v:40:y:2012:i:3:p:314-327
    DOI: 10.1016/j.omega.2011.07.003
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    References listed on IDEAS

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    Cited by:

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    3. Sinha, Priyank & Kumar, Sameer & Chandra, Charu, 2023. "Strategies for ensuring required service level for COVID-19 herd immunity in Indian vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 304(1), pages 339-352.
    4. Songtao Zhang & Yanting Hou & Siqi Zhang & Min Zhang, 2017. "Fuzzy Control Model and Simulation for Nonlinear Supply Chain System with Lead Times," Complexity, Hindawi, vol. 2017, pages 1-11, September.
    5. Dmitry Ivanov & Boris Sokolov & Inna Solovyeva & Alexandre Dolgui & Ferry Jie, 2016. "Dynamic recovery policies for time-critical supply chains under conditions of ripple effect," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7245-7258, December.
    6. Saraeian, Shideh & Shirazi, Babak & Motameni, Homayun, 2019. "Adaptive control of criticality infrastructure in automatic closed-loop supply chain considering uncertainty," International Journal of Critical Infrastructure Protection, Elsevier, vol. 25(C), pages 102-124.
    7. Fang, Xin & Zhang, Cheng & Robb, David J. & Blackburn, Joseph D., 2013. "Decision support for lead time and demand variability reduction," Omega, Elsevier, vol. 41(2), pages 390-396.
    8. Garcia Salcedo, Carlos Andres & Ibeas Hernandez, Asier & Vilanova, Ramón & Herrera Cuartas, Jorge, 2013. "Inventory control of supply chains: Mitigating the bullwhip effect by centralized and decentralized Internal Model Control approaches," European Journal of Operational Research, Elsevier, vol. 224(2), pages 261-272.
    9. Cannella, Salvatore & Dominguez, Roberto & Framinan, Jose M., 2017. "Inventory record inaccuracy – The impact of structural complexity and lead time variability," Omega, Elsevier, vol. 68(C), pages 123-138.

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