Combining Probabilistic Forecasts of Intermittent Demand
arxiv(2023)
摘要
In recent decades, new methods and approaches have been developed for
forecasting intermittent demand series. However, the majority of research has
focused on point forecasting, with little exploration into probabilistic
intermittent demand forecasting. This is despite the fact that probabilistic
forecasting is crucial for effective decision-making under uncertainty and
inventory management. Additionally, most literature on this topic has focused
solely on forecasting performance and has overlooked the inventory
implications, which are directly relevant to intermittent demand. To address
these gaps, this study aims to construct probabilistic forecasting combinations
for intermittent demand while considering both forecasting accuracy and
inventory control utility in obtaining combinations and evaluating forecasts.
Our empirical findings demonstrate that combinations perform better than
individual approaches for forecasting intermittent demand, but there is a
trade-off between forecasting and inventory performance.
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