A comparison of maximum likelihood, exponential smoothing and Bayes forecasting procedures in inventory modelling
- 1 January 1974
- journal article
- research article
- Published by Taylor & Francis in International Journal of Production Research
- Vol. 12 (5) , 607-622
- https://doi.org/10.1080/00207547408919579
Abstract
This paper compares four major schemes used for forecasting mean demand to be used as input into an inventory model so that ‘ optimum ’ stockage levels can be obtained. The inventory model is the classical order up to S, infinite horizon model with carry-over from period to period and complete back-ordering. Maximum likelihood, exponential smoothing, standard Bayes and adaptive Bayes schemes are used and results, via Monte Carlo simulation, are obtained on the average costs per period for (1) stationary demand, (2) long-term trend and (3) ‘ shock ’ changes in mean demand.Keywords
This publication has 1 reference indexed in Scilit:
- Bayes sequential design of stock levelsNaval Research Logistics Quarterly, 1969