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

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

European Journal of Operational Research, 2023, vol. 304, issue 2, 515-524

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.

Keywords: Inventory; Correlated demand; Stochastic programming; Mixed integer linear programming; Martingale model of forecast evolution (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:304:y:2023:i:2:p:515-524

DOI: 10.1016/j.ejor.2022.04.011

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