A Bayesian approach to demand forecasting to optimize spare parts inventory that requires periodic replenishment is examined relative to a non-Bayesian approach when the demand rate is unknown. That is, optimal inventory levels are decided using these two approaches at consecutive time...

One aspect of forecasting intermittent demand for slow-moving inventory that has not been investigated to any depth in the literature is seasonality. This is due in part to the reliability of computed seasonal indexes when many of the periods have zero demand. This chapter proposes an innovative...

When forecasting intermittent demand the method derived by Croston (1972) is often cited. Previous research favorably compared Croston's forecasting method for demand with simple exponential smoothing assuming a nonzero demand occurs as a Bernoulli process with a constant probability. In...