This book covers three different problems that companies commonly face when managing their inventories: the introduction of new inventory policies in existing inventory systems, the use of algorithmic advice by human planners, and the accuracy of master data on which inventory models rely. By using mathematical optimization, behavioral experiments, and machine learning, the developed approaches support the successful implementation of state-of-the-art inventory research in practice.
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