A Non-Parametric Approach for Setting Safety Stock Levels

Approximations for the Lead Time Variance: A Forecasting and Inventory Evaluation

“…Examples consist of Chebyshev's Inequality (Gardner, 1988) or bootstrapping methods, with the latter finding successful use in approximating the intervals of a known demand process (Thombs and Schucany, 1990), and also performing well in setting reorder points (Wang and Rao, 1992) and meeting service levels (Fricker and Goodhart, 2000). A bootstrapping procedure for estimating safety stocks under skewed or multimodal distributions is proposed by Saldanha et al (2020) as a remedy for demand processes that exhibit these departures from the typical assumptions surrounding demand. Similarly, Kernel Density Estimation has been used to directly estimate quantiles from the forecast error distribution to inform the calculation of safety stock (Trapero et al, 2018).…”