Expert Systems in Intermittent Demand Forecasting

Abstract

The main aim of the article was to propose an expert intermittent demand forecasting system. This system is based on stochastic simulation but also has many adjustments that might be treated as expert corrections. The presented forecasting system was applied in a company that sells mostly tools and work clothes. The number of forecasted items is over 16,000. The expert system was compared with the most popular intermittent demand forecasting methods (based on exponential smoothing) such as Croston’s, SBA, TSB or SES methods. For each of these methods a separate forecasting system was constructed. Smoothing factors as well as initial values for all forecasts were optimized. Forecasting accuracy measures taking into account the specificity of an intermittent demand time series were applied. Also, a new forecast error measure (scaled Absolute Mean Error) was proposed and used in the comparisons.