报告题目：Constant-Order Policies for Lost-Sales Inventory Models with Random Supply Functions: Asymptotics and Heuristic

主讲人：姚大成（中国科学院数学与系统科学研究院）

邀请人：杨建奎

时间：2019年1月14日（周一13:00-14:00）

地点：主楼804

报告摘要：

We consider an infinite-horizon lost-sales inventory model where the supply takes positive lead time and is a random function of the order quantity (e.g., random yield/capacity). The optimal policy for this model is computationally intractable; and no heuristic has been proposed in the literature. In this paper, we focus on a simple class of constant-order policies (COP) that place the same order in every period, regardless of the system state. Under some assumptions on the random supply function, we prove that the best COP is asymptotically optimal with large lead times and the optimality gap converges to zero exponentially fast in the lead time. We also prove that, if the mean supply capacity is less than the mean demand, then the best COP is also asymptotically optimal with large penalty cost; otherwise, the long-run average cost of the best COP asymptotically increases at the rate of square-root of the penalty cost. Further, we construct a simple heuristic COP and show that it performs very close to the best COP. Finally, we provide a numerical study to derive further insights into the performance of the best COP. (Joint work with Jinzhi Bu (CUHK) and Xiting Gong (CUHK))

报告人简介：

姚大成，中科院数学与系统科学研究院副研究员，是应用概率、随机控制等研究领域的青年才俊。在Math. OR, IEEE A.C.,SIAM opt.等领域内的顶级期刊上发表多篇文章。