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000772080 019__ $$a949883557
000772080 020__ $$a9783658140625$$q(electronic book)
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000772080 1001_ $$aEngelmeyer, Torben,$$eauthor.
000772080 24510 $$aManaging intermittent demand /$$cTorben Engelmeyer.
000772080 264_1 $$aFachmedien :$$bSpringer Gabler,$$c2016.
000772080 300__ $$a1 online resource.
000772080 336__ $$atext$$btxt$$2rdacontent
000772080 337__ $$acomputer$$bc$$2rdamedia
000772080 338__ $$aonline resource$$bcr$$2rdacarrier
000772080 4901_ $$aSpringer Gabler Research
000772080 504__ $$aIncludes bibliographical references.
000772080 5050_ $$aClassification Approaches to Identify Intermittent Demand Series -- Consistent Forecast-Based Inventory Model -- Extensive Comparison of the Inventory Performance Among Different Forecast/Inventory Model Combinations.
000772080 506__ $$aAccess limited to authorized users.
000772080 520__ $$aThis work aims to increase the service level and to reduce the inventory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory decision of intermittent demand series. In an extensive simulation study the new model is compared with a wide range of conventional forecast/inventory model combinations. By using the consistent approach, the mean inventory level is lowered whereas the service level is increased. Additionally, a modern multi-criteria inventory classification scheme is presented to distinguish different demand series clusters. Contents Classification Approaches to Identify Intermittent Demand Series Consistent Forecast-Based Inventory Model Extensive Comparison of the Inventory Performance Among Different Forecast/Inventory Model Combinations Target Group Students and researchers interested in business analytics and operations management Inventory managers and supply chain experts The Author Dr. Torben Engelmeyer works as a research assistant at the chair of International Economics - University of Wuppertal, Germany.
000772080 588__ $$aOnline resource; title from PDF title page (viewed May 18, 2016).
000772080 650_0 $$aInventory control$$xMathematical models.
000772080 650_0 $$aInventories$$xManagement.
000772080 77608 $$iPrint version:$$aEngelmeyer, Torben$$tManaging Intermittent Demand$$dWiesbaden : Springer Fachmedien Wiesbaden,c2016$$z9783658140618
000772080 830_0 $$aSpringer Gabler research.
000772080 852__ $$bebk
000772080 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-658-14062-5$$zOnline Access$$91397441.1
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000772080 983__ $$aOnline
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