Dynamic re-order point inventory control with lead-time uncertainty: analysis and empirical investigation

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.

Keywords:

• stock control
• forecasting
• lead-time demand
• simulation
• empirical analysis

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/).