会议议程

会议时间：3月16日晚上20:30-22:30（北京时间）

腾讯会议ID：544-791-673, 密码：706708

标题：Assign-to-Seat: Dynamic Capacity Control for Selling High-Speed Train Tickets

3月16日晚上20:30-22:30，将于以下平台同步直播。

直播链接1（寇享学术）：https://www.koushare.com/lives/room/480747

直播链接2（B站）：https://live.bilibili.com/26422082

温馨提示：
因网速问题限制，可能会遇到画质、声音问题，感谢理解支持！ 

【专家简介】

Prof. Zizhuo Wang is a Professor and Associate Dean (Education) at the School of Data Science, CUHK-Shenzhen. He obtained his bachelor's degree in Mathematics from Tsinghua University in 2007, and his Ph.D. degree in Operations Research from Stanford University in 2012. Prior to joining CUHK-Shenzhen, he was an Associate Professor (with tenure) in the Department of Industrial and Systems Engineering at the University of Minnesota. His research interests mainly focus on optimization and stochastic modeling, especially with applications to pricing and revenue management. He has published over 40 papers in top journal in the field of operations research and management science, and has been the Associate Editors or Senior Editors for the top journals such as Management Science, Operations Research, Manufacturing and Service Operations Management and Production and Operations Management. Prof. Wang has extensive experiences in applying operations research methods in industry. He has participated in projects with IBM, Seagate, American Express in the US, and has been a quantitative research at the Wall Street. In 2016, he co-founded Cardinal Operations with others, which served over 100 enterprises (including JD.com, SF Express, Didi, Huawei, China Southern Airlines) to provide data-driven decision support service and products.【报告摘要】

We consider a revenue management problem that arises from the selling of high-speed train tickets in China. Compared with traditional network revenue management problems, the new feature of our problem is the assign-to-seat restriction. That is, each request, if accepted, must be assigned instantly to a single seat throughout the whole journey, and later adjustment is not allowed. When making decisions, the seller needs to track not only the total seat capacity available but also the status of each seat. We build a modified network revenue management model for this problem. First, we study a static problem in which all requests are given. Although the problem is NP-hard in general, we identify conditions for solvability in polynomial time. We then introduce a bid-price control policy based on a novel maximal sequence principle. This policy accommodates nonlinearity in bid prices and, as a result, yields a more accurate approximation of the value function than a traditional bid-price control policy does. Finally, we combine a dynamic view of the maximal sequence with the static solution of a primal problem to propose a re-solving a dynamic primal policy that can achieve uniformly bounded revenue loss under mild assumptions. Numerical experiments using both synthetic and real data document the advantage of the policies we propose for improving the efficiency of capacity allocation.

主办方：中国科学技术大学科技商学院

协办方：中国科学技术大学管理学院，国际金融研究院

承办方：现代物流与供应链安徽省重点实验室