A MODIFIED BOOTSTRAP METHOD FOR INTERMITTENT DEMAND FORECASTING FOR RARE SPARE PARTS.
- Publisher:
- Publishing Horizons
- Publication Type:
- Journal Article
- Citation:
- International Journal of Industrial Engineering, 2017, 24, (2), pp. 245-254
- Issue Date:
- 2017
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An effective inventory management requires timely and accurate forecasting of demand for parts or items. In many realworld scenarios, however, the demand for rare, high-cost spare parts are scarce and erratic, making it highly challenging to
perform a reliable forecast for intermittent demand. Studies in the past offered two approaches to such intermittent demand
forecasting: a traditional approach to estimating demand parametrically, and a non-parametric approach that estimates the
distribution of demands. The bootstrap method is considered to be one of the key non-parametric methods available. Despite
its usefulness, however, application of conventional bootstrap methods in intermittent demand forecasting does not take into
account any existing dependent structures in lead time demand, leading to inaccurate forecasting. In this paper, we suggest a
new bootstrap method that takes into consideration the unique characteristics of intermittent demand to improve forecasting
performance. We conclude by demonstrating the applicability of suggested new method through the results of a simple case
experiment
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