Division for Industrial Engineering and Computer Sciences FORECASTING RISK ANALYSIS FOR SUPPLY CHAINS WITH INTERMITTENT DEMAND

The paper focuses on the forecasting risk analysis in the supply chains with the intermittent demand, which is typical for the inventory management of the “slow moving items” such as service parts or high-priced capital goods. The adopted demand model is based on the generalised beta-binomial distribution, which is capable to incorporate the additive distortions in the demand historical records as parameters. For this settings, there are proposed explicit expressions for the forecasting risk and the prediction function, which minimises the error impact on the risk. The efficiency of the proposed approach is confirmed by computer simulation and is illustrated by an application example for forecasting of the intermittent demand values for car spare parts.