Extended Beta-binomial Model for Demand Forecasting of Multiple Slow-Moving Items with Low Consumption and Short Requests History

Abstract : The paper considers the problem of modeling the lead-time demand for the multiple slow-moving inventory items in the case when the available demand history is very short, and a large percentage of items has only zero records. The Bayesian approach is used to overcome the mentioned problems with the past demand data: it is proposed to use the beta-binomial model to predict the lead-time demand probability distribution for each item. Further, an extension of this model is developed that allows accounting for the prior information regarding the maximum expected probability of demand per period. Parameter estimation and Bayesian forecasting routines are derived for the new model. The efficiency and practical significance of the obtained results is proved by the simulation study.
Type de document :
Rapport
2005
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https://hal-emse.ccsd.cnrs.fr/emse-00679895
Contributeur : Florent Breuil <>
Soumis le : vendredi 16 mars 2012 - 15:24:40
Dernière modification le : mardi 23 octobre 2018 - 14:36:08

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  • HAL Id : emse-00679895, version 1

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Alexandre Dolgui, Maxim Pashkevich. Extended Beta-binomial Model for Demand Forecasting of Multiple Slow-Moving Items with Low Consumption and Short Requests History. 2005. 〈emse-00679895〉

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