New approaches to inventory control: algorithms, asymptotics and robustness
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The fundamental problem of managing an inventory over time in the presence of stochastic demand is one of the core problems of operations research. This thesis is motivated by the need (in both government and industry) to understand such complex inventory systems used to model many of society's most important problems. In particular, we investigate simple, efficient and robust inventory policies for several fundamental models commonly used in the study of stochastic inventory systems. Some of these policies have been already implemented in practice and we provide strong theoretic support for their practical utilization in industry. Furthermore, the results on the performance of these policies often yield a rule-of-thumb that is applicable in a variety of settings.