Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing

dc.contributor.author	Δογάνης, Φίλιππος	el
dc.contributor.author	Αλεξανδρίδης, Αλέξανδρος Π.	el
dc.contributor.author	Πατρινός, Παναγιώτης Κ.	el
dc.contributor.author	Σαρίμβεης, Χαράλαμπος Κ.	el
dc.date.accessioned	2015-06-04T12:26:07Z
dc.date.available	2015-06-04T12:26:07Z
dc.date.issued	2015-06-04
dc.identifier.uri	http://hdl.handle.net/11400/15053
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.source	http://www.elsevier.com/	en
dc.subject	Dairy products
dc.subject	Evolutionary computation
dc.subject	Fresh milk
dc.subject	Genetic algorithms
dc.subject	neural networks
dc.subject	Sales forecasting
dc.subject	Γαλακτοκομικά προϊόντα
dc.subject	Εξελικτική υπολογιστική
dc.subject	Φρέσκο γάλα
dc.subject	Γενετικοί αλγόριθμοι
dc.subject	Νευρωνικά δίκτυα
dc.subject	Πρόβλεψη πωλήσεων
dc.title	Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing	en
heal.type	journalArticle
heal.classification	Technology
heal.classification	Chemical technology
heal.classification	Τεχνολογία
heal.classification	Χημική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://skos.um.es/unescothes/C00565
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Χημική τεχνολογία
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85035453
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh95003989
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh92002377
heal.keywordURI	http://lod.nal.usda.gov/12606
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85116727
heal.identifier.secondary	DOI: 10.1016/j.jfoodeng.2005.03.056
heal.language	en
heal.access	campus
heal.publicationDate	2006-07
heal.bibliographicCitation	DOGANIS, P., ALEXANDRIDIS, A.P., PATRINOS, P.K. & SARIMVEIS, H.K. (2006). Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing. Journal of Food Engineering. [online] 75 (2). p. 196-204. Available from: http://www.elsevier.com/[Accessed 21/06/2005]	en
heal.abstract	Due to the strong competition that exists today, most manufacturing organizations are in a continuous effort for increasing their profits and reducing their costs. Accurate sales forecasting is certainly an inexpensive way to meet the aforementioned goals, since this leads to improved customer service, reduced lost sales and product returns and more efficient production planning. Especially for the food industry, successful sales forecasting systems can be very beneficial, due to the short shelf-life of many food products and the importance of the product quality which is closely related to human health. In this paper we present a complete framework that can be used for developing nonlinear time series sales forecasting models. The method is a combination of two artificial intelligence technologies, namely the radial basis function (RBF) neural network architecture and a specially designed genetic algorithm (GA). The methodology is applied successfully to sales data of fresh milk provided by a major manufacturing company of dairy products.	en
heal.publisher	Elsevier	en
heal.journalName	Journal of Food Engineering	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true