A note on Tempelmeier's β-service measure under non-stationary stochastic demand
For researchers and practitioners using fill rate constraints in inventory optimization, this note highlights a flaw in a widely-cited model.
This note identifies that Tempelmeier's MIP model for β-service level under non-stationary demand does not align with the standard fill rate definition, potentially leading to sub-optimal policies, as shown via a numerical example.
Tempelmeier (2007) considers the problem of computing replenishment cycle policy parameters under non-stationary stochastic demand and service level constraints. He analyses two possible service level measures: the minimum no stock-out probability per period (α-service level) and the so called "fill rate", that is the fraction of demand satisfied immediately from stock on hand (β-service level). For each of these possible measures, he presents a mixed integer programming (MIP) model to determine the optimal replenishment cycles and corresponding order-up-to levels minimizing the expected total setup and holding costs. His approach is essentially based on imposing service level dependent lower bounds on cycle order-up-to levels. In this note, we argue that Tempelmeier's strategy, in the β-service level case, while being an interesting option for practitioners, does not comply with the standard definition of "fill rate". By means of a simple numerical example we demonstrate that, as a consequence, his formulation might yield sub-optimal policies.