Another look at estimators for intermittent demand
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- 作者：Fotios Petropoulosa ; petropoulosf@cardiff.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Nikolaos Kourentzesb ; n.kourentzes@lancaster.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Konstantinos Nikolopoulosc ; k.nikolopoulos@bangor.ac.uk" class="auth_mail" title="E-mail the corresponding author
- 关键词：Intermittent demand ; Temporal aggregation ; Variance reduction ; Decomposition
- 刊名：International Journal of Production Economics
- 出版年：2016
- 出版时间：November 2016
- 年：2016
- 卷：181
- 期：part_PA
- 页码：154-161
- 全文大小：630 K
文摘
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We propose a new aggregation framework for intermittent demand forecasting.
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Inverse ADIDA (iADIDA) reduces the variance of the demand sizes.
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iADIDA is expected to be particularly effective for erratic demand.
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Forecasting and stock control evaluations are performed on two large data sets.