Practice-driven solutions for inventory management problems in data-scarce environments
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Citation
Abstract
Many firms are challenged to make inventory decisions with limited data, and high customer service level requirements. This thesis focuses on heuristic solutions for inventory management problems in data-scarce environments, employing rigorous mathematical frameworks and taking advantage of the information that is available in practice but often ignored in literature. We define a class of inventory models and solutions with demonstrable value in helping firms solve these challenges.