Speaker: Professor Kay Chen Tan
Title: Learnable Evolutionary Algorithms for Complex Multiobjective Optimization
Time: 16:00-17:00, September 1, 2022 (Thursday)
Website: https://meeting.tencent.com/dm/GycDo4JgEHPP（Tencent meeting）
(meeting number:264 688 331）
Abstract:
Evolutionary algorithms characterized by a population-based iterative search approach have been recognized as effective tools for addressing multiobjective optimization problems (MOPs) in different scenarios. Since the number of solutions grows exponentially with the number of objective functions and the search space expands exponentially with the number of design variables, learning to customize efficient environmental selection strategies in the objective space as well as simplifying the search space and enhancing the search capability in the variable space are crucial for good scalability in solving complex problems. Besides, as optimization problems seldom exist in isolation, the experience of solving one problem (or task) may learn useful knowledge to assist the optimization of other related ones. This is consistent with the learning behavior of human beings that useful knowledge from past experiences can be exploited to solve relevant problems at hand and potential synergies may be excavated when facing multiple seemingly unrelated problems. This talk will highlight some of our recent works on scalable and learnable multiobjective optimization to tackle various types of complex problems, i.e., many-objective optimization problems, large-scale MOPs, and multitasking MOPs. Some discussions on future research directions will also be given.
Personal Introduction:
Kay Chen Tan is currently a Chair Professor (Computational Intelligence) and Associate Head (Research and Developments) of the Department of Computing, The Hong Kong Polytechnic University. He has co-authored 7 books and published over 230 peer-reviewed journal papers. Prof. Tan is currentlythe Vice-President (Publications) ofIEEE Computational Intelligence Society, USA. He was the Editor-in-Chief of IEEE Transactions on Evolutionary Computation from 2015-2020, and IEEE Computational Intelligence Magazine from 2010-2013. Prof. Tan is an IEEE Fellow, an IEEE Distinguished Lecturer Program (DLP) speaker, and an Honorary Professor at the University of Nottingham in UK. He also serves as the Chief Co-Editor of Springer Book Series on Machine Learning: Foundations, Methodologies, and Applications.
[Editor: Xiaohan Liu]