Titlebook: Managing Intermittent Demand; Torben Engelmeyer Book 2016 Springer Fachmedien Wiesbaden 2016 Logistik.Langsamdreher.Optimierung.Prognose.B

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Introduction,roduction changed the view on inventories from assets, which convert to cash, to pure cost drivers. With an increasing availability of data, concepts like Efficient Consumer Response and Predictive Analytics resulted in the need for optimized decisions based on uncertain demand information.

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Inventory Managements are minimal. It is a crucial function in most companies, and in general it cannot be separated from other functions. For example, the optimal inventory policy will certainly depend on promotion campaigns conducted by the marketing department.

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Conclusiond the forecast model. On the one hand, major efforts are made to consider all the features of the demand series to produce the most accurate forecasts. On the other hand, the majority of inventory frameworks are accompanied by rigid stochastic assumptions, such as Gaussian or gamma distributed lead

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Book 2016model combinations. By using the consistent approach, the mean inventory level is lowered whereas the service level is increased. Additionally, a modern multi-criteria inventory classification scheme is presented to distinguish different demand series clusters. .

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Book 2016cast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory de

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entory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used

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