Intermittent demand forecasting

dc.contributor.author	Συντέτος, Άρης Α.	el
dc.contributor.author	Boylan, John E.	en
dc.date.accessioned	2015-03-11T15:57:48Z
dc.date.available	2015-03-11T15:57:48Z
dc.date.issued	2015-03-11
dc.identifier.uri	http://hdl.handle.net/11400/7833
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	Forecasting
dc.subject	Πρόβλεψη
dc.subject	Απογραφή
dc.subject	Διαλείπουσα
dc.subject	Ζήτηση
dc.subject	Inventory
dc.subject	Intermittent
dc.subject	Demand
dc.title	Intermittent demand forecasting	en
heal.type	conferenceItem
heal.secondaryTitle	size - interval methods based on averaging and smoothing	en
heal.generalDescription	Είναι πρακτικά συνεδρίου	el
heal.generalDescription	Αθήνα, 26-27 Μαΐου 2003. ΤΕΙ Αθήνας	el
heal.classification	Economy
heal.classification	Business enterprises
heal.classification	Οικονομία
heal.classification	Διοίκηση επιχειρήσεων
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85040879
heal.classificationURI	http://lod.nal.usda.gov/5266
heal.classificationURI	N/A-Οικονομία
heal.classificationURI	N/A-Διοίκηση επιχειρήσεων
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh00005779
heal.contributorName	Φράγκος, Χρήστος Κ. (1949-) ( υπεύθ. οργ.)	el
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Διοίκησης και Οικονομίας, Τμήμα Διοίκησης Επιχειρήσεων. Κατεύθυνση Διοίκησης Επιχειρήσεων	el
heal.publicationDate	2003-05
heal.bibliographicCitation	Boylan, J. E., and Syntetos, A. A. (2003) Intermittent demand forecasting: size - interval methods based on averaging and smoothing. In proceedings of the 1st international conference quantitative methods in industry and commerce. Athens, 26 - 27 May 2003. TEI of Athens. pp.87-96.	en
heal.abstract	For faster moving non-trended products, it is well established that Single Exponential Smoothing is more accurate than Simple Moving Averages for short-term forecasting (Makridakis et al (1982)). However, much of the benefit that derives from SES can be obtained by the simpler expedient of using a combination of Simple Moving Averages (Johnston et al (1999), Boylan and Johnston (2003)). In an intermittent demand setting, Croston (1972) proposed using a ratio of size and interval estimates, both based on exponential smoothing. This method has been used extensively in practice. Recently, Syntetos and Boylan (2001) showed that this method is biased and proposed an alternative estimator, using a correction factor. In this paper, a new estimator is proposed, based on a ratio of Simple Moving Averages of Size and Interval, allowing different lengths of averaging to be used on the numerator and denominator if necessary. A correction factor is presented, to ensure that the method is approximately unbiased. The performance of the two estimators is assessed using empirical data from the perspective of forecasting accuracy, approaches, is outlined.	en
heal.publisher	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας	el
heal.publisher	TEI of Athens	en
heal.fullTextAvailability	true
heal.conferenceName	1o Διεθνές Συνέδριο: Ποσοτικές Μέθοδοι στη Βιομηχανία και τις Εμπορικές Επιχειρήσεις	el
heal.conferenceName	1st International Conference: Quantitative Methods in Industry and Commerce	en
heal.conferenceItemType	full paper