Hierarchical Estimation as Basis for Hierarchical Forecasting

L.W.G. Strijbosch, R.M.J. Heuts, J.J.A. Moors

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Abstract

In inventory management, hierarchical forecasting (HF) is a hot issue : families of items are formed for which total demand is forecasted; total forecast then is broken up to produce forecasts for the individual items.Since HF is a complicated procedure, analytical results are hard to obtain; consequently, most literature is based on simulations and case studies.This paper succeeds in following a more theoretical approach by simplifying the problem : we consider estimation instead of forecasting.So, from a random sample we estimate both total demand and the fraction of this total that individual items take; multiplying these two quantities gives a new estimate of individual demand.Then our research question is: can aggregation of items, followed by fractioning, lead to more accurate estimates of individual demand?Thirdly, a more practical situation is investigated by means of simulation.
Original languageEnglish
Place of PublicationTilburg
PublisherOperations research
Number of pages15
Volume2006-86
Publication statusPublished - 2006

Publication series

NameCentER Discussion Paper
Volume2006-86

Keywords

  • hierarchical forecasting
  • aggregation
  • top-down approach

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    Strijbosch, L. W. G., Heuts, R. M. J., & Moors, J. J. A. (2006). Hierarchical Estimation as Basis for Hierarchical Forecasting. (CentER Discussion Paper; Vol. 2006-86). Operations research.