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Table of contents (7 chapters)
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Front Matter
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Fundamentals and Methodology
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Front Matter
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Empirical Analysis
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Front Matter
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Back Matter
Keywords
About this book
This 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.
Authors and Affiliations
About the author
Dr. Torben Engelmeyer works as a research assistant at the chair of International Economics - University of Wuppertal, Germany.
Bibliographic Information
Book Title: Managing Intermittent Demand
Authors: Torben Engelmeyer
DOI: https://doi.org/10.1007/978-3-658-14062-5
Publisher: Springer Gabler Wiesbaden
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer Fachmedien Wiesbaden 2016
Softcover ISBN: 978-3-658-14061-8Published: 11 May 2016
eBook ISBN: 978-3-658-14062-5Published: 02 May 2016
Edition Number: 1
Number of Pages: XV, 157
Number of Illustrations: 65 b/w illustrations
Topics: Logistics, Supply Chain Management, Operations Research/Decision Theory