综合运输系统运营管理研究组学术讲座
题目:Newsvendor under Mean-Variance Ambiguity and Misspecification
考虑模糊性和模型误设的报童模型
时间: 2025年9月19日10：30
地点: 同济大厦A楼306教室
讲座摘要:
Consider a newsvendor problem with an unknown demand distribution. When addressing the issue of distributional uncertainty, we distinguish ambiguity under which the newsvendor does not differentiate demand distributions of common distributional characteristics (e.g., mean and variance) and misspecification under which such characteristics might be misspecified (due to, e.g., estimation error and/or distribution shift). Focusing on the popular mean-variance ambiguity set and optimal-transport cost for the misspecification, we derive the closed-form optimal order quantity that generalizes the solution of the seminal Scarf model under only ambiguity aversion. We quantify the finite-sample performance guarantee, which consists of two parts: the in-sample optimal value and the out-of-sample effect of misspecification that can be decoupled into estimation error and distribution shift. This theoretically justifies the necessity of incorporating misspecification aversion in a non-stationary environment, which is also well demonstrated in our experiments with real-world retailing data. Our framework can be extended to consider multiple products, distributional characteristics specified via optimal transport, and misspecification measured by phi-divergence.
演讲嘉宾简介:
Zhi Chen is an Associate Professor in the CUHK Business School and an Research Associate in CUHK Shenzhen Research Institute, the Chinese University of Hong Kong. His research interests include (1) developing models and designing algorithms for decision-making under uncertainty with different levels of data availability as well as applications in business, economics, finance, and operations; (2) how to compete or cooperate in joint activities such as resource allocation and risk management. His research has been funded by NSFC and Hong Kong Research Grants Council.
