主题：Supermodularity in Two-Stage Distributionally Robust Optimization

主讲人：香港科技大学 戚瑾助理教授

主持人：大数据研究院 徐亮教授

时间：2021年7月8日（周四）14:00-15:00

举办地点：腾讯会议，会议ID：828 2924 9673

主办单位：大数据研究院 科研处

主讲人简介：

戚瑾，香港科技大学工业工程与决策科学系助理教授。获新加坡国立大学博士学位，清华大学学士及硕士学位。主要从事鲁棒优化的理论和应用，及医疗运营等方面的研究。

内容简介：

In this paper, we solve a class of two-stage distributionally robust optimization problems which have the property of supermodularity. We exploit the explicit worst-case expectation of supermodular functions and derive the worst-case distribution for the robust counterpart. This enables us to develop an efficient method to obtain an exact optimal solution of these two-stage problems. We also show that the optimal scenariowise segregated affine decision rule returns the same optimal value in our setting. Further, we provide a necessary and sufficient condition for checking whether any given two-stage optimization problem has the supermodularity property. We apply this framework to several classic problems, including the multi-item newsvendor problem, the facility location design problem, the lot-sizing problem on a network, the appointment scheduling problem and the assemble-to-order problem. While these problems are typically computationally challenging, they can be solved efficiently using our approach.

本次报告针对带有超模性的两阶段分布鲁棒优化问题，提出高效精确算法，并证明了最优决策准则结构。随后用于求解多商品报童模型，设施选址问题，网络中的生产批量模型等。