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【Mingli Lecture, 2023, Issue 35】5-12 Professor Wang Zizhuo, Chinese University of Hong Kong (Shenzhen): Assign to Seat:

Report Title: Assign to Seat: Dynamic Capacity Control for Selling High Speed Train Tickets

Time: May 12th (Friday) 15:00-17:00 PM

Location: Conference Room 317, Main Building, Zhongguancun Campus

Conference ID: # Tencent Conference ID: 796-174-557

Reported by: Professor Wang Zizhuo, Vice Dean of the School of Data Science, The Chinese University of Hong Kong (Shenzhen)

Introduction to report content: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.

Reported by:

Wang Zizhuo is a professor and deputy dean of the School of Data Science at the Chinese University of Hong Kong (Shenzhen), as well as a co-founder and Chief Technology Officer of Shanshu Technology. Professor Wang Zizhuo graduated from the Department of Mathematics and Applied mathematics of Tsinghua University in 2007 with a bachelor's degree, and obtained a doctorate in Management science and Engineering from Stanford University in 2012. Prince Zhuo was an associate professor in the Department of Industrial and Systems Engineering at the University of Minnesota. Currently, he is the director of Guangdong Provincial Key Laboratory of Artificial Intelligence Mathematics and Physics, and the deputy director of the Theory Institute of Big data Research Institute.

Professor Wang Zizhuo's main research direction is Operations research and the application of machine learning. He has published more than 50 articles in the top international magazines of Operations research and Management science, and served as the editorial board member of top Management science magazines such as management science, operations research, M&SOM, POMS, etc. Professor Wang Zizhuo has led or is currently leading multiple research projects, including those from the National Natural Science Foundation of China and the National Natural Science Foundation of the United States, with a total amount of over ten million RMB.

Professor Wang Zizhuo has rich experience in the industry. Since 2016, Wang Zizhuo has co founded Shanshu Technology and served as CTO. Over the past six years, he has provided intelligent decision-making consulting and services for over a hundred enterprises in China, including leading domestic companies such as JD, SF Express, Didi, Huawei, and China Southern Airlines.

(Undertaken by: Department of Management science and Logistics, Digital Economy Innovation Research Center of the Third Institute of Beijing Science and Technology, Scientific Research and Academic Center)

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