On the performance of binomial and beta-binomial models of demand forecasting for multiple slow-moving inventory items

Industrial Engineering and Computer Sciences Division (G2I) ON PERFORMANCE OF BINOMIAL AND BETA-BINOMIAL MODELS OF LEAD-TIME DEMAND FORECASTING FOR MULTIPLE SLOW-MOVING ITEMS WITH SHORT REQUESTS HISTORY

The paper deals with the lead-time demand forecasting for inventory management of multiple slow-moving items in the case when the available demand history is very short. Two stochastic models of demand are compared: (i) the first based on the “population-averaged” binomial distribution of requests (the traditional approach); and (ii) the second based on the beta-binomial probability distributio...

Industrial Engineering and Computer Sciences Division (G2I) EXTENDED BETA-BINOMIAL MODEL FOR DEMAND FORECASTING OF MULTPLE SLOW-MOVING ITEMS WITH LOW CONSUMPTION AND SHORT REQUESTS HISTORY

The paper considers the problem of modeling the lead-time demand for the multiple slow-moving inventory items in the case when the available demand history is very short, and a large percentage of items has only zero records. The Bayesian approach is used to overcome the mentioned problems with the past demand data: it is proposed to use the beta-binomial model to predict the lead-time demand p...

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...

Beta-Binomial Model and Its Generalizations in the Demand Forecasting for Multiple Slow-Moving

Forecasting the Intermittent Demand for Slow-Moving Items

Organizations with large-scale inventory systems typically have a large proportion of items for which demand is intermittent and low volume. We examine different approaches to forecasting for such products, paying particular attention to the need for inventory planning over a multi-period lead-time when the underlying process may be nonstationary. This emphasis leads to consideration of predict...