题　目：Assortment Optimization with Downward Feasible Constraints: Approximation Algorithms Based on Independent Demands

嘉　宾：高品 助理教授 香港中文大学（深圳）

主持人：许欢 教授 上海交通大学安泰经济与管理学院

时　间：2025年11月21日（周五）10:00-11:30

地　点：安泰楼B207室

内容简介：

Given the intricate nature of consumer behavior and the operational constraints faced by businesses, some industry professionals often rely on the independent demand model (IDM) to simplify demand estimation and assortment optimization. However, this approach does not account for cannibalization effects among products. To address this limitation, we propose an IDM-based optimization variant that uniformly adjusts the unit revenue contributions of all products.  For last-choice regular models that meet certain bounding conditions, our approximation algorithm---requiring solving only two linear programs---achieves the best possible performance guarantees when the assortment constraints are totally unimodular (TUM) and downward feasible. More generally, we propose extensions for non-TUM constraints and for cases where the bounding conditions are difficult to determine. Beyond its practical simplicity, the proposed methodology also facilitates the development of efficient approximation algorithms for several previously studied problems, either by relaxing assumptions or improving approximation ratios. Comprehensive computational tests indicate that the proposed approximation algorithms offer exceptional performance. Furthermore, an examination of a real-world dataset shows that our algorithms, developed from models with enhanced predictive accuracy, yield better optimization results.

演讲人简介：

Dr. Pin Gao is an assistant professor in the School of Data Science at the Chinese University of Hong Kong, Shenzhen. His research focuses on choice modeling and platform economics, with recent work integrating modern machine learning methods into pricing and assortment optimization. He received his Ph.D. from the Hong Kong University of Science and Technology in 2021. His research has been supported by the National Natural Science Foundation of China (Young Scientists Fund, Categories B and C) and by industry partners including Meituan, Feng1.com, and Didi.

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