Contextual Ranking and Selection


    Department of Systems Engineering and Engineering Management

                       The Chinese University of Hong Kong


Date: Friday, November 3, 2023, 4:30pm to 5:30pm HKT

Venue: ERB 513, The Chinese University of Hong Kong

Title: Contextual Ranking and Selection

Speaker: Dr. Siyang Gao, City University of Hong Kong, Associate Editor of the journals IEEE Transactions on Automation Science and Engineering and Journal of Simulation



The ranking and selection (R&S) problem seeks to efficiently select the best simulated system design among a finite number of alternatives. It is a well-established problem in simulation-based optimization, and has wide applications in the production, service and operation management. In this research, we consider R&S in the presence of context, where the context corresponds to some input information to the simulation model and can influence the performance of each design. This is a new and emerging problem in simulation for personalized decision making. The goal is to determine the best allocation of the simulation budget among various contexts and designs so as to efficiently identify the best design for all the contexts that might possibly appear. We call it contextual ranking and selection (CR&S). We utilize the OCBA approach in R&S, and solve the problem by developing appropriate objective measures, identifying the rate-optimal budget allocation rule and analyzing the convergence of the selection algorithm. We numerically test the performance of the proposed algorithm via a set of abstract and real-world problems, and show the superiority of the algorithm in solving these problems and obtaining real-time decisions.



Siyang Gao received the B.S. degree in Mathematics from Peking University in 2009 and the Ph.D. degree in Industrial Engineering from University of Wisconsin-Madison in 2014. Dr. Gao is the Associate Head and an Associate Professor with the Department of Systems Engineering, City University of Hong Kong. His research is devoted to simulation optimization, machine learning and their applications in healthcare management. His work has appeared in Operations Research, Manufacturing & Service Operations Management, INFORMS Journal on Computing, Production and Operations Management, IEEE Transactions on Automatic Control, etc. He is a recipient of the Best Conference Paper Award at the IEEE Conference on Automation Science and Engineering in 2019, Best Paper Award at the International Conference on Logistics and Maritime Systems in 2019, and the Best Young Faculty Paper Award at the International Research Conference on Systems Engineering and Management Science in 2018. Dr. Gao is currently serving as an Associate Editor of the journals IEEE Transactions on Automation Science and Engineering and Journal of Simulation.


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Friday, November 3, 2023 - 16:30