[Time] 14:00 – 15:00, March 19 (Thursday), 2020
Lotus Pond Rain Classroom: W141WB
ZOOM ID: 320 388 996
Tecent ID：984 027 963
[Speaker] Dr. L. Jeff Hong
[Host] Dr. Lei Zhao
[Title] Large-scale ranking and selection in parallel computing environments
Note: We will register the seminar for the attendees by the record in Lotus Pond Rain Classroom.
On one hand, large-scale ranking and selection (R&S) problems
require a large amount of computation. On the other hand, parallel
computing environments that provide a large capacity for computation are
becoming prevalent today and they are accessible by ordinary users.
Therefore, solving large-scale R&S problems in parallel computing
environments has emerged as an important research topic in recent years.
However, directly implementing traditional stage-wise procedures and
fully-sequential procedures in parallel computing environments may
encounter problems, because either the procedures require too many
simulation observations or the procedures’ selection structures induce
too many comparisons and too frequent communications among the
processors. In this paper, inspired by the knockout-tournament
arrangement of tennis Grand Slam tournaments, we develop new R&S
procedures to solve large-scale problems in parallel computing
environments. We show that no matter whether the variances of the
alternatives are known or not, our procedures can theoretically achieve
the lowest growth rate on the expected total sample size with respect to
the number of alternatives and thus are optimal in rate. Moreover,
common random numbers (CRNs) can be easily adopted in our procedures to
further reduce the total sample size. Meanwhile, the comparison time in
our procedures is negligible compared to the simulation time, and our
procedures barely request for communications among the processors.
Prof. Jeff Hong received his bachelor’s degree from Tsinghua University
and Ph.D. from Northwestern University. He is currently with School of
Management and School of Data Science at Fudan University, holding the
positions of Fudan Distinguished Professor and Hongyi Chair Professor.
He was Chair Professor of Management Sciences at City University of Hong
Kong, and Professor and Director of Financial Engineering Laboratory at
the Hong Kong University of Science and Technology. Prof. Hong’s
research focuses on the areas of operations research, data science, and
financial engineering and risk management. He has published over 60
papers on leading academic journals and conference proceedings,
including 20 papers on the UTD journals. He has won numerous awards,
including Outstanding Research Award from Operations Research Society of
China, Outstanding Simulation Publication Award from INFORMS Simulation
Society, Operations Best Paper Award from Institute of Industrial
Engineers. Prof. Hong is currently an Area Editor of Operations
Research, an Associate Editor of Management Science and ACM Transactions
on Modeling and Computer Simulation, and the President-Elect of INFORMS
All interested are welcome!