Managing intermittent demand represents a very critical task in term of forecasting and stock control due to the variability both of demand sizes and demand arrivals. In this pa-per the forecasting issue is tackled by comparing different extrapolative forecasting ap-proaches. In particular, the SARIMA model (Seasonal Autoregressive Integrated Moving Average) is applied on 60 real time series by means of the TRAMO-SEATS procedure, which is a versatile and automatic procedure allowing a quick identification of the best performing SARIMA model for each item. The forecasting performances are then compared with those obtained by the well-known methods of Croston and Syntetos-Boylan, which represent two modified versions of the simple exponential smoothing specifically introduced for estimating the mean demand per period in case of intermittent demand profiles. Furthermore, the aggre-gation of forecasts in lower-frequency ‘time buckets’ is implemented in order to evaluate how these methods behave on aggregated time horizons.

APPLICATION OF TRAMO-SEATS AUTOMATIC PROCEDURE FOR FORECASTING INTERMITTENT DEMAND PATTERNS / Lolli, Francesco; Gamberini, Rita; Regattieri, A.; Rimini, Bianca. - ELETTRONICO. - (2014), pp. 1435-1445. ((Intervento presentato al convegno 1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014 tenutosi a Kos Island (Greece) nel 4th-6th June.

APPLICATION OF TRAMO-SEATS AUTOMATIC PROCEDURE FOR FORECASTING INTERMITTENT DEMAND PATTERNS

LOLLI, Francesco;GAMBERINI, Rita;RIMINI, Bianca
2014

Abstract

Managing intermittent demand represents a very critical task in term of forecasting and stock control due to the variability both of demand sizes and demand arrivals. In this pa-per the forecasting issue is tackled by comparing different extrapolative forecasting ap-proaches. In particular, the SARIMA model (Seasonal Autoregressive Integrated Moving Average) is applied on 60 real time series by means of the TRAMO-SEATS procedure, which is a versatile and automatic procedure allowing a quick identification of the best performing SARIMA model for each item. The forecasting performances are then compared with those obtained by the well-known methods of Croston and Syntetos-Boylan, which represent two modified versions of the simple exponential smoothing specifically introduced for estimating the mean demand per period in case of intermittent demand profiles. Furthermore, the aggre-gation of forecasts in lower-frequency ‘time buckets’ is implemented in order to evaluate how these methods behave on aggregated time horizons.
1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014
Kos Island (Greece)
4th-6th June
1435
1445
Lolli, Francesco; Gamberini, Rita; Regattieri, A.; Rimini, Bianca
APPLICATION OF TRAMO-SEATS AUTOMATIC PROCEDURE FOR FORECASTING INTERMITTENT DEMAND PATTERNS / Lolli, Francesco; Gamberini, Rita; Regattieri, A.; Rimini, Bianca. - ELETTRONICO. - (2014), pp. 1435-1445. ((Intervento presentato al convegno 1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014 tenutosi a Kos Island (Greece) nel 4th-6th June.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1025914
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