Elucidate structure in intermittent demand series

Kourentzes, Nikolaos and Athanasopoulos, George (2021) Elucidate structure in intermittent demand series. European Journal of Operational Research, 288 (1). pp. 141-152. ISSN 0377-2217

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Intermittent demand forecasting has been widely researched in the context of spare parts management. However, it is becoming increasingly relevant to many other areas, such as retailing, where at the very disaggregate level time series may be highly intermittent, but at more aggregate levels are likely to exhibit trends and seasonal patterns. The vast majority of intermittent demand forecasting methods are inappropriate for producing forecasts with such features. We propose using temporal hierarchies to produce forecasts that demonstrate these traits at the various aggregation levels, effectively informing the resulting intermittent forecasts of these patterns that are identifiable only at higher levels. We conduct an empirical evaluation on real data and demonstrate statistically significant gains for both point and quantile forecasts.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Additional Information:
This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 288, 1, 2021 DOI: 10.1016/j.ejor.2020.05.046
Uncontrolled Keywords:
?? forecastingtemporal aggregationtemporal hierarchiesforecast combinationforecast reconciliationmodelling and simulationmanagement science and operations researchinformation systems and management ??
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Deposited On:
22 May 2020 12:55
Last Modified:
15 Jul 2024 20:40