Beschreibung:
ABSTRACTA computer simulation experiment was conducted to evaluate and compare seven individual item forecasting models across five different demand patterns. Results indicate the best model varies depending upon the demand pattern, the time period forecast, the noise level of the demand pattern, and to a lesser extent the measure of forecast error. Across all demand patterns, exponential double smoothing was best for the long run forecast and at least second best for the short run regardless of noise level in the demand patterns. Analysis of models within a demand pattern yielded, in most cases, several models as ranking equally well. The adaptive model developed here did not perform as well as some other models. For example, it ranked no better than third on a step function demand pattern.