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In recent decades, new methods and approaches have been developed forforecasting intermittent demand series. However, the majority of research hasfocused on point forecasting, with little exploration into probabilisticintermittent demand forecasting. This is despite the fact that probabilisticforecasting is crucial for effective decision-making under uncertainty andinventory management. Additionally, most literature on this topic has focusedsolely on forecasting performance and has overlooked the inventoryimplications, which are directly relevant to intermittent demand. To addressthese gaps, this study aims to construct probabilistic forecasting combinationsfor intermittent demand while considering both forecasting accuracy andinventory control utility in obtaining combinations and evaluating forecasts.Our empirical findings demonstrate that combinations perform better thanindividual approaches for forecasting intermittent demand, but there is atrade-off between forecasting and inventory performance.

Combining Probabilistic Forecasts of Intermittent Demand