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Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches

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  • Qiu, Ruozhen
  • Sun, Minghe
  • Lim, Yun Fong

Abstract

This study considers a finite-horizon single-product periodic-review inventory management problem with demand distribution uncertainty. The problem is formulated as a dynamic program and the existence of an optimal (s, S) policy is proved. The corresponding dynamic robust counterpart models are then developed for the box and the ellipsoid uncertainty sets. These counterpart models are transformed into tractable linear and second-order cone programs, respectively. The effectiveness and practicality of the proposed robust optimization approaches are validated through a numerical study.

Suggested Citation

  • Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
  • Handle: RePEc:eee:ejores:v:261:y:2017:i:3:p:880-892
    DOI: 10.1016/j.ejor.2017.02.027
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    4. Xiang, Mengyuan & Rossi, Roberto & Martin-Barragan, Belen & Tarim, S. Armagan, 2018. "Computing non-stationary (s, S) policies using mixed integer linear programming," European Journal of Operational Research, Elsevier, vol. 271(2), pages 490-500.
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    7. Zheng, Meimei & Su, Zhiyun & Wang, Dong & Pan, Ershun, 2024. "Joint maintenance and spare part ordering from multiple suppliers for multicomponent systems using a deep reinforcement learning algorithm," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
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