講座主題：Globalized Distributionally Robust Optimization
講座時間：2023年9月1日（周五）下午4點
講座地點：學院一樓107會議室
主講人：王曙明 中國科學院大學 經濟與管理學院
講座摘要：
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.
王曙明簡介：中國科學院大學經濟與管理學院 教授，主要從事魯棒優化、隨機規劃研究及其在選址、物流與供應鏈管理、健康醫療管理等領域的應用。研究成果分別發表于Production and Operations Management, INFORMS Journal on Computing, Transportation Science, IISE Transactions, Naval Research Logistics, IEEE Trans. Cybernetics等權威雜志上。目前擔任期刊《Computers & Operations Research》領域主編 (Area Editor).