A comparison of maximum likelihood, exponential smoothing and Bayes forecasting procedures in inventory modelling
作者:
DONALD GROSS,
ROBERTJAY CRAIG,
期刊:
International Journal of Production Research
(Taylor Available online 1974)
卷期:
Volume 12,
issue 5
页码: 607-622
ISSN:0020-7543
年代: 1974
DOI:10.1080/00207547408919579
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
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 toS, 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.
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