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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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