日期：7月6日（星期四）

时间：14:00 – 15:00

主题：Online Learning for On-demand Vehicle sharing Networks with Pricing

主讲人：高翔宇

主持人：邓天虎

语言：中文

参加方式：舜德楼512教室

讲座介绍：We consider the pricing problem in on-demand vehicle sharing networks with online demand learning. When there is no prior information available on the demand functions, the main challenge in designing an online learning algorithm is how to explore the demand functions while maintaining a balanced network. We address this challenge with an online learning algorithm adapted from the ellipsoid method. In our algorithm, the search subroutine is based on the idea of bisection and the Upper Confidence Bound, which can locate the price associated with a desired demand level for each type of trip, as characterized by the trip origin and destination, and estimate the gradient information at the price point. By carefully selecting the center of the ellipsoid for each iteration, we can ensure that the expected revenue improves and maintain a balanced network in each iteration. We prove the upper bound of regret our learning algorithm given a fixed workload parameter. The numerical performance of the algorithm is illustrated using synthetic data. We also discuss extensions to the online learning algorithm in which the workload parameter is unknown.

主讲人介绍：Xiangyu Gao is an assistant professor in the Department of Decision Sciences and Managerial Economics at The Chinese University of Hong Kong (CUHK) Business School. He obtained his doctoral degree in industrial engineering from the University of Illinois at Urbana Champaign and a bachelor’s degree in systems engineering and engineering management from CUHK. His research interests include inventory control, data-driven learning algorithms, and revenue management. His work has been published in top-tier academic journals such as Management Science and Operations Research.