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Rostami-Tabar, Bahman; Babai, Mohamed Zied; Syntetos, Argyrios; Ducq, Yves (2014)
Publisher: Wiley-Blackwell
Languages: English
Types: Article
Subjects: HD
Earlier research on the effects of nonoverlapping temporal aggregation on demand forecasting showed the benefits associated with such an approach under a stationary AR(1) or MA(1) processes for decision making conducted at the disaggregate level. The first objective of this note is to extend those important results by considering a more general underlying demand process. The second objective is to assess the conditions under which aggregation may be a preferable approach for improving decision making at the aggregate level as well. We confirm the validity of previous results under more general conditions, and we show the increased benefit resulting from forecasting by temporal aggregation at lower frequency time units.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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