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A mathematical programming-based solution method for the nonstationary inventory problem under correlated demand

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  • Xiang, Mengyuan
  • Rossi, Roberto
  • Martin-Barragan, Belen
  • Tarim, S. Armagan

Abstract

This paper extends the single-item single-stocking location nonstationary stochastic inventory problem to relax the assumption of independent demand. We present a mathematical programming-based solution method built upon an existing piecewise linear approximation strategy under the receding horizon control framework. Our method can be implemented by leveraging off-the-shelf mixed-integer linear programming solvers. It can tackle demand under various assumptions: the multivariate normal distribution, a collection of time-series processes, and the Martingale Model of Forecast Evolution. We compare against exact solutions obtained via stochastic dynamic programming to demonstrate that our method leads to near-optimal plans.

Suggested Citation

  • Xiang, Mengyuan & Rossi, Roberto & Martin-Barragan, Belen & Tarim, S. Armagan, 2023. "A mathematical programming-based solution method for the nonstationary inventory problem under correlated demand," European Journal of Operational Research, Elsevier, vol. 304(2), pages 515-524.
    • Handle: RePEc:eee:ejores:v:304:y:2023:i:2:p:515-524
    DOI: 10.1016/j.ejor.2022.04.011
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    References listed on IDEAS

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