We study adaptive policies that handle dynamic inventory and price controls when the random demand for discrete nonperishable items is unknown. Pure inventory control is achieved by targeting newsvendor ordering quantities that correspond to empirical demand distributions learned over time. On this basis we conduct the more complex joint inventory-price control, where demand-affecting prices await to be evaluated as well. We identify policies that strive to balance between exploration and exploitation, and measure their performances via regrets, i.e., the prices to pay for not knowing demand distributions a priori over a given horizon. Multiple bounds are derived on regrets' growth rates; they vary with how thoroughly unknown the demand distributions are and whether nonperishability has indeed been accounted for. Our simulation study illustrates order-of-magnitude differences between pure inventory and joint inventory-price controls in terms of regret growth rates.

中文翻译：

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涉及离散的不易腐烂物品的未知需求的动态库存和价格控制

我们研究当离散的不易腐烂物品的随机需求未知时处理动态库存和价格控制的自适应策略。通过定位新闻供应商的订购数量来实现纯粹的库存控制，该数量对应于随着时间推移而获得的经验需求分配。在此基础上，我们进行更复杂的库存价格联合控制，在此期间，还需要评估影响需求的价格。我们确定旨在在勘探与开发之间取得平衡的政策，并通过遗憾（即在给定范围内不知道先验需求而付出的代价）来衡量其绩效。后悔的增长速度有多重界限。它们随需求分布的未知程度以及是否确实考虑了不朽性而变化。