Journal
INTERNATIONAL JOURNAL OF FORECASTING
Volume 20, Issue 3, Pages 375-387Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/S0169-2070(03)00013-X
Keywords
accuracy; bootstrapping; Croston's method; exponential smoothing; intermittent demand; inventory; spare parts; service parts
Categories
Ask authors/readers for more resources
A fundamental aspect of supply chain management is accurate demand forecasting. We address the problem of forecasting intermittent (or irregular) demand, i.e. random demand with a large proportion of zero values. This pattern is characteristic of demand for service parts inventories and capital goods and is difficult to predict. We forecast the cumulative distribution of demand over a fixed lead time using a new type of time series bootstrap. To assess accuracy in forecasting an entire distribution, we adapt the probability integral transformation to intermittent demand. Using nine large industrial datasets, we show that the bootstrapping method produces more accurate forecasts of the distribution of demand over a fixed lead time than do exponential smoothing and Croston's method. (C) 2003 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available