Intermittent demand forecast: Robustness assessment for group method of data handling

Demand forecasting is a key ingredient of supply chain process and plays an important role in synchronized planning and reduced bullwhip effect. Intermittent demand forecasting is a special case of demand forecasting when there are several periods of zero and uneven demand for a product in historical time. Developing a model to forecast intermittent demand has been a challenge, and models of various vintages have been proposed. In this paper, we develop a model for intermittent demand forecasting invoking the Group Method of Data Handling (GMDH) and perform a comparative evaluation of the robustness of this model in comparison to classical models in vogue.