Items with irregular and sporadic demand profiles are frequently tackled by companies, given the necessity of proposing wider and wider mix, along with characteristics of specific market fields (i.e. when spare parts are manufactured and sold). Furthermore, a new company entering into the market is featured by irregular customers orders. Hence, consistent efforts are spent with the aim of correctly forecasting and managing irregular and sporadic products demand. In this paper, the problem of correctly forecasting customers orders is analyzed by empirically comparing existing forecasting techniques. The case of items with irregular demand profiles, coupled with seasonality and trend components, is investigated. Specifically, forecasting methods (i.e. Holt-Winters approach and (S)ARIMA) available for items with seasonality and trend components are empirically analyzed and tested in the case of data coming from the industrial field and characterized by intermittence. Hence, in the conclusions section, well performing approaches are addressed.

FORECASTING OF SPORADIC DEMAND PATTERNS WITH SEASONALITY AND TREND COMPONENTS: AN EMPIRICAL COMPARISON BETWEEN HOLT-WINTERS AND (S)ARIMA METHODS / Gamberini, Rita; Lolli, Francesco; Rimini, Bianca; Sgarbossa, F.. - In: MATHEMATICAL PROBLEMS IN ENGINEERING. - ISSN 1024-123X. - ELETTRONICO. - -:(2010), pp. Article ID 579010-doi:10.1155/2010/579010. [10.1155/2010/579010]

FORECASTING OF SPORADIC DEMAND PATTERNS WITH SEASONALITY AND TREND COMPONENTS: AN EMPIRICAL COMPARISON BETWEEN HOLT-WINTERS AND (S)ARIMA METHODS

GAMBERINI, Rita;LOLLI, Francesco;RIMINI, Bianca;
2010

Abstract

Items with irregular and sporadic demand profiles are frequently tackled by companies, given the necessity of proposing wider and wider mix, along with characteristics of specific market fields (i.e. when spare parts are manufactured and sold). Furthermore, a new company entering into the market is featured by irregular customers orders. Hence, consistent efforts are spent with the aim of correctly forecasting and managing irregular and sporadic products demand. In this paper, the problem of correctly forecasting customers orders is analyzed by empirically comparing existing forecasting techniques. The case of items with irregular demand profiles, coupled with seasonality and trend components, is investigated. Specifically, forecasting methods (i.e. Holt-Winters approach and (S)ARIMA) available for items with seasonality and trend components are empirically analyzed and tested in the case of data coming from the industrial field and characterized by intermittence. Hence, in the conclusions section, well performing approaches are addressed.
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Article ID 579010
doi:10.1155/2010/579010
FORECASTING OF SPORADIC DEMAND PATTERNS WITH SEASONALITY AND TREND COMPONENTS: AN EMPIRICAL COMPARISON BETWEEN HOLT-WINTERS AND (S)ARIMA METHODS / Gamberini, Rita; Lolli, Francesco; Rimini, Bianca; Sgarbossa, F.. - In: MATHEMATICAL PROBLEMS IN ENGINEERING. - ISSN 1024-123X. - ELETTRONICO. - -:(2010), pp. Article ID 579010-doi:10.1155/2010/579010. [10.1155/2010/579010]
Gamberini, Rita; Lolli, Francesco; Rimini, Bianca; Sgarbossa, F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/643266
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