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Another look at estimators for intermittent demand

Petropoulos, Fotios, Kourentzes, Nikolaos and Nikolopoulos, Konstantinos 2016. Another look at estimators for intermittent demand. International Journal of Production Economics 181 (Part A) , pp. 154-161. 10.1016/j.ijpe.2016.04.017

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Abstract

In this paper we focus on forecasting for intermittent demand data. We propose a new aggregation framework for intermittent demand forecasting that performs aggregation over the demand vol- umes, in contrast to the standard framework that employs temporal (over time) aggregation. To achieve this we construct a transformed time series, the inverse intermittent demand series. The new algorithm is expected to work best on erratic and lumpy demand, as a result of the variance reduction of the non-zero demands. The improvement in forecasting performance is empirically demonstrated through an extensive evaluation in more than 8,000 time series of two well-researched spare parts data sets from the automotive and defence sectors. Furthermore, a simulation is per- formed so as to provide a stock-control evaluation. The proposed framework could nd popularity among practitioners given its suitability when dealing with clump sizes. As such it could be used in conjunction with existing popular forecasting methods for intermittent demand as an exception handling mechanism when certain types of demand are observed.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > HD Industries. Land use. Labor
Publisher: Elsevier
ISSN: 0925-5273
Date of First Compliant Deposit: 20 April 2016
Date of Acceptance: 19 April 2016
Last Modified: 09 Jul 2020 15:16
URI: http://orca.cf.ac.uk/id/eprint/89429

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