A new approach to forecasting intermittent demand for service parts inventories

By T. Willemain, C. N. Smart, Henry Schwarz. 2004

402 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7431ede2868522f595ae45218e4fbc1c6c24aa36

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Simple versus complex forecasting: The evidence (2015, neutral): “Syntetos, Babai and Gardner (this issue) compare forecasts from simple, no trend, exponential smoothing and two other simple techniques developed specifically for intermittent demand forecasts, with those from a complex method reported by Willemain, Smart, and Schwarz (2004).”
Intermittent demand forecasts with neural networks (2013, methodology): “Willemain et al. (2004) identified intermittent demand in several scenarios, such as heavy machinery and respective spare parts, aircraft service parts, electronics, maritime spare parts, etc, while Syntetos and Boylan (2005) explored intermittency in the automotive spare parts.”
The accuracy of intermittent demand estimates (2005, background): “Willemain, Smart, and Schwarz (2004) argue that b ... we need to assess the quality not of a point forecast of the mean but of a forecast of the entire distributionQ, but they concede that it is impossible to compare this on an item-specific basis.”
25 years of time series forecasting (2006, methodology): “Willemain et al. (2004) proposed a bootstrap procedure for intermittent demand data which was found to be more accurate than either SES or Croston’s method on the nine series evaluated.”
Forecasting and operational research: a review (2008, neutral): “Willemain et al (2004) developed a patented non-parametric forecasting method for intermittent demand data.”
EXPONENTIAL SMOOTHING: THE STATE OF THE ART, PART II (2006, neutral): “The last study in which exponential smoothing did not perform well is by Willemain, Smart, and Schwarz (2004), who claimed that their patented bootstrap method made significant improvements in forecast accuracy over the N-N and Croston methods.”
On the demand distributions of spare parts (2012, neutral): “At this point, it is important to note that some non-parametric procedures have also been suggested in the literature to forecast intermittent demand requirements (e.g. Willemain et al. 2004, Porras and Dekker 2008).”
25 Years of IIF Time Series Forecasting: A Selective Review (2005, background): “Willemain, T.R., C.N. Smart and H.F. Schwarz (2004), ‘A new approach to forecasting intermittent de- mand for service parts inventories’, International Journal of Forecasting, 20, 375–387.”