Impact of temporal aggregation on stock control performance of intermittent demand estimators: empirical analysis.

Babai, Mohamed Zied, Ali, Mohammad Mojiballah and Nikolopoulos, Konstantinos (2012) Impact of temporal aggregation on stock control performance of intermittent demand estimators: empirical analysis. OMEGA International Journal of Management Science, 40 (6). pp. 713-721. ISSN 0305-0483

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Abstract

Intermittent demand is characterized by occasional demand arrivals interspersed by time intervals during which no demand occurs. These demand patterns pose considerable difficulties in terms of forecasting and stock control due to their compound nature, which implies variability both in terms of demand arrivals and demand sizes. An intuitively appealing strategy to deal with such patterns from a forecasting and stock control perspective is to aggregate demand in lower-frequency ‘time buckets’, thereby reducing the presence of zero observations. In this paper, we investigate the impact of forecasting aggregation on the stock control performance of intermittent demand patterns. The benefit of the forecasting aggregation approach is empirically assessed by means of analysis on a large demand dataset from the Royal Air Force (UK). The results show that the aggregation forecasting approach results in higher achieved service levels as compared to the classical forecasting approach. Moreover, when the combined service-cost performance is considered, the results also show that the former approach is more efficient than the latter, especially for high target service levels.

Item Type:	Article
Depositing User:	ULCC Admin
Date Deposited:	04 May 2012 12:30
Last Modified:	11 Jul 2022 08:33
URI:	https://bnu.repository.guildhe.ac.uk/id/eprint/9987

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