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Forecast combinatio...
Forecast combinations for intermittent demand
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- Petropoulos, Fotios (author)
- Lancaster Centre for Forecasting, Lancaster University Management School, Lancaster University, Lancaster, United Kingdom
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- Kourentzes, Nikolaos (author)
- Lancaster Centre for Forecasting, Lancaster University Management School, Lancaster University, Lancaster, United Kingdom
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(creator_code:org_t)
- 2017-12-21
- 2015
- English.
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In: Journal of the Operational Research Society. - : Taylor & Francis. - 0160-5682 .- 1476-9360. ; 66:6, s. 914-924
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https://eprints.lanc...
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https://urn.kb.se/re...
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Abstract
Subject headings
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- 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.
Subject headings
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)
Keyword
- classification
- combining
- forecasting
- intermittent demand
- parametric methods
- temporal aggregation
- Benchmarking
- Classification (of information)
- Time series
- Forecast combinations
- Forecasting performance
- Parametric method
- Standard practices
- Time series classifications
Publication and Content Type
- ref (subject category)
- art (subject category)
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