讲座主题：Globalized Distributionally Robust Optimization

讲座时间：2023年9月1日（周五）下午4点

讲座地点：学院一楼107会议室

主讲人：王曙明 中国科学院大学 经济与管理学院

讲座摘要：
We extend the notion of globalized robustness to consider distributional information beyond the support of the ambiguous probability distribution. We propose the globalized distributionally robust counterpart that disallows any (resp., allows limited) constraint violation for distributions residing (resp., not residing) in the ambiguity set. By varying its inputs, our proposal recovers several existing perceptions of parameter uncertainty. Focusing on the type-1 Wasserstein distance, we show that the globalized distributionally robust counterpart has an insightful interpretation in terms of shadow price of globalized robustness, and it can be seamlessly integrated with many popular optimization models under uncertainty without incurring any extra computational cost. Such computational attractiveness also holds for other ambiguity sets, including the ones based on probability metric, optimal transport, φ-divergences, or moment conditions, as well as the event-wise ambiguity set. Numerical studies on an adaptive network lot-sizing problem demonstrate the modeling flexibility of our proposal and its emphases on globalized robustness to constraint violation.

王曙明简介：中国科学院大学经济与管理学院 教授，主要从事鲁棒优化、随机规划研究及其在选址、物流与供应链管理、健康医疗管理等领域的应用。研究成果分别发表于Production and Operations Management, INFORMS Journal on Computing, Transportation Science, IISE Transactions, Naval Research Logistics, IEEE Trans. Cybernetics等权威杂志上。目前担任期刊《Computers & Operations Research》领域主编 (Area Editor).