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An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming

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  • Placido dos Santos, Felipe Silva
  • Oliveira, Fabricio

Abstract

This paper presents the development of an enhanced L-Shaped method applied to an inventory management problem that considers a replenishment control system based on the periodic review (R, S) policy. We consider single-item one-echelon problems with uncertain demands and partial backorder that are modeled using two-stage stochastic programming. To enable the consideration of large-scale problems, the classical single-cut L-Shaped method and its extended multi-cut form were initially applied. Preliminary computational results indicated that the classical L-Shaped method outperformed its multi-cut counterpart, even though the former required more iterations to converge to the optimal solution. This observation inspired the development of the techniques presented for enhancing the L-Shape method, which consist of the combination of a novel acceleration technique with an efficient formulation and valid inequalities for the proposed model. Numerical experiments suggest that the proposed approach significantly reduced the computational time required to solve large-scale problems.

Suggested Citation

  • Placido dos Santos, Felipe Silva & Oliveira, Fabricio, 2019. "An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming," European Journal of Operational Research, Elsevier, vol. 275(2), pages 677-693.
    • Handle: RePEc:eee:ejores:v:275:y:2019:i:2:p:677-693
    DOI: 10.1016/j.ejor.2018.11.053
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    3. Visentin, Andrea & Prestwich, Steven & Rossi, Roberto & Tarim, S. Armagan, 2021. "Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming," European Journal of Operational Research, Elsevier, vol. 294(1), pages 91-99.
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