Dynamic Inventory Control with Fixed Setup Costs and Unknown Discrete Demand Distribution
研究了新产品或新经济环境下需求分布未知时，企业如何通过基于历史数据的经验分布调整订货决策，在固定设置成本下平衡长期稳定与信息更新，实现遗憾最小化。
When a new product has just been introduced or the economy has just entered a new phase, a firm is often at a loss as to what the underlying demand pattern has become let alone how best to respond to it. In “Dynamic Inventory Control with Fixed Setup Costs and Unknown Discrete Demand Distribution,” Davoodi, Katehakis, and Yang faced off this challenging problem by tailoring ordering decisions to empirical distributions formed out of past demand observations. In the presence of fixed setup costs, however, an (s,S) policy optimal in the conventional known-distribution setting would take many periods for its long-term benefit to be realized. Therefore, a good online policy has to balance between letting ordering decisions settle for long periods and adjusting them frequently to take advantage of newly available information. When properly balanced, such policies could indeed achieve tight bounds for the performance measure of regret.