Solving Robust Inventory Problems
نویسنده
چکیده
Solving Robust Inventory Problems In this work we consider setting the optimal inventory control policies for a single buffer when demand is uncertain, in a robust framework. Unlike traditional inventory models we do not assume that the demand is random with a known distribution. Instead, demand can take values from a given uncertainty set. Our objective is to find the policy that minimize the maximum cost that is attainable by the demand vectors in our uncertainty set. We consider the problem for two different types of policies which are very common in practice and present a family of algorithms based on decomposition that scale well to problems with hundreds of time periods. We also present theoretical results on more general models.
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