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  • JORS 2014 (preprint)

    Rights statement: This is a pre-print of an article published in Journal of the Operational Research Society. The definitive publisher-authenticated version is available online at: http://www.palgrave-journals.com/jors/journal/v66/n6/full/jors201462a.html

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Forecast combinations for intermittent demand

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>06/2015
<mark>Journal</mark>Journal of the Operational Research Society
Issue number6
Volume66
Number of pages11
Pages (from-to)914-924
Publication statusPublished
Early online date11/06/14
Original languageEnglish

Abstract

Intermittent demand is characterised by infrequent demand arrivals, where many periods have zero demand, coupled with varied demand sizes. The dual source of variation renders forecasting for intermittent demand a very challenging task. Many researchers have focused on the development of specialised methods for intermittent demand. However, apart from a case study on hierarchical forecasting, the effects of combining, which is a standard practice for regular demand, have not been investigated. This paper empirically explores the efficiency of forecast combinations in the intermittent demand context. We examine both method and temporal combinations of forecasts. The first are based on combinations of different methods on the same time series, while the latter use combinations of forecasts produced on different views of the time series, based on temporal aggregation. Temporal combinations of single or multiple methods are investigated, leading to a new time series classification, which leads to model selection and combination. Results suggest that appropriate combinations lead to improved forecasting performance over single methods, as well as simplifying the forecasting process by limiting the need for manual selection of methods or hyper-parameters of good performing benchmarks. This has direct implications for intermittent demand forecasting in practice.

Bibliographic note

This is a pre-print of an article published in Journal of the Operational Research Society. The definitive publisher-authenticated version is available online at: http://www.palgrave-journals.com/jors/journal/v66/n6/full/jors201462a.html