期刊
INTERNATIONAL JOURNAL OF FORECASTING
卷 20, 期 3, 页码 375-387出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/S0169-2070(03)00013-X
关键词
accuracy; bootstrapping; Croston's method; exponential smoothing; intermittent demand; inventory; spare parts; service parts
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据