Abstract
A new forecast-based dynamic inventory control approach is discussed in this paper. In this approach, forecasts and forecast uncertainties are assumed to be exogenous data known in advance at each period over a fixed horizon. The control parameters are derived by using a sequential procedure. The merits of this approach as compared to the classical one are presented. We focus on a single-stage and single-item inventory system with non-stationary demand and lead-time uncertainty. A dynamic re-order point control policy is analysed based on the new approach and its parameters are determined for a given target cycle service level (CSL). The performance of this policy is assessed by means of empirical experimentation on a large demand data set from the pharmaceutical industry. The empirical results demonstrate the benefits arising from using such a policy and allow insights to be gained into other pertinent managerial issues.
Acknowledgements
The research conducted by the first two authors (M.Z. Babai and A.A. Syntetos) was supported by the Engineering and Physical Sciences Research Council (EPSRC, UK) grant EP/D062942/1. (More information on this project may be found at: http://www.mams.salford.ac.uk/CORAS/Projects/Forecasting/).