Abstract
The stock diffusion theory (SDT) is a mathematical model, based on the Fokker Planck equation, that makes it possible to accurately estimate stock-out probability, even in case of highly heteroscedastic demand. The paper shows how the SDT can be exploited to formulate an innovative continuous review policy, which can be effectively used for inventory management. Since the model needs, as input, the trend of the mean μ(t) and that of the variance σ2(t) of the demand, the paper also introduces two alternative (and robust) ways to estimate these functions, starting from the time series of the demand. Lastly, analysis of variance, based on an extensive Monte-Carlo simulation, is performed to compare the proposed approach with respect to a set of standard continuous review policies taken as benchmark. Results confirm the robustness of the proposed policy and its applicability in many practical cases.
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