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Towards Optimal Inventory Control under Censored Demand: A Biased Sample-Average Approximation Approach
We study data-driven multi-period lost-sales inventory control under censored demand, where a stockout reveals only that demand exceeded the stocking level. We develop a unified, model-based framework for policy learning from censored data, built on a new cost decomposition for base-stock policies a
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