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Evaluating the Lead Time Demand Distribution for (r, Q) Policies Under Intermittent Demand

Evaluating the Lead Time Demand Distribution for (r, Q) Policies Under Intermittent Demand,Yasin Unlu,Manuel D. Rossetti

Evaluating the Lead Time Demand Distribution for (r, Q) Policies Under Intermittent Demand  
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This paper examines the use of standard (r, Q) inventory control policies for situations involving intermittent highly variable demand that is known to have sporadic or infrequent occurrences along with high variability for the number of units demanded. The paper investigates how well the inventory control model behaves under various demand scenarios. The key to the application of inventory models to intermittent scenarios is how well the lead-time demand distribution can be modeled. A number of distributions, namely, normal, gamma, Poisson and negative binomial that might be applicable in the case of intermittent and highly variable demand are examined. Historical data from industry was analyzed and used to develop realistic demand scenarios for the purpose of experimentation. Based on empirically estimated parameters, the experimental results compare performance measures; namely, fill rate and average backorder levels which are generated under each inventory control policy with a corresponding lead time demand distribution. The evaluation of the accuracy of these measures is also compared via a simulation study. These representational errors cause the planned for operational performance to not be met. This is a problem in the use of inventory models in general, but it is especially so in the case of intermittent demand where the characterization of the lead-time demand distribution is even more problematic. Demand for products that have sporadic or infrequent occurrences along with high variability for the number of units demanded is often termed intermittent demand. Intermittent demand data is also characterized by time series that have many time periods with zero demand. Intermittent demand often occurs for slower moving inventory items and for the demand processes resulting from repair operations. Various approaches have been developed in the literature to cope with the inventory situations involving intermittent demand (3-5). Inventory control under intermittent demand is a challenging task, which is mostly due to the nature of the demand pattern. The transaction (demand incidence) variability (sporadicity) and also demand size variability (lumpiness) are two factors that together make it hard to model the lead time demand distribution, and accordingly set an appropriate inventory control policy. Due to these
Published in 2009.
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