Time: 14: 00 – 15: 00 (JST), Oct 16, 2023.
Location: R205, Education & Research Building No. 8, Muroran Institute of Technology, 27-1 Mizumoto-cho, Muroran, Hokkaido, 0508585 Japan.
- IEEE Muroran Institute of Technology Student Branch
- IEEE Sapporo Section Young Professionals (YP)
- Emerging Networks and Systems Laboratory (ENeS), Muroran Institute of Technology
Topic: Evolutionary Multi-Objective Optimization: Basic Ideas and Recent Hot Topics
Speaker: Liemeng Pang, Research Associate, Southern University of Science and Technology (SUSTech), China
Multi-objective optimization problems are commonly found in many real-world applications. These problems involve the simultaneous optimization of multiple conflicting objective functions. Consequently, they do not yield a single optimal solution but rather a set of trade-off solutions. The trade-off solutions are often defined using the Pareto dominance relation and are known as Pareto optimal solutions. When mapped to the objective space, they form the Pareto front. Evolutionary Multi-Objective Optimization (EMO) algorithms have been a popular approach for solving multi-objective optimization problems. Thanks to their population-based search nature, EMO algorithms can obtain a set of nondominated solutions in a single run, which is then used to approximate the Pareto front. This talk will give a comprehensive introduction on the fundamental concepts of evolutionary multi-objective optimization including commonly used strategies in designing EMO algorithms. Additionally, the talk will also cover some recent hot topics and advancements in the field of evolutionary multi-objective optimization.
Lie Meng Pang received her Bachelor of Engineering degree in Electronic and Telecommunication Engineering and Ph.D. degree in Electronic Engineering from the Faculty of Engineering, University Malaysia Sarawak, in 2012 and 2018, respectively. She is currently a Research Associate with the Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), China. Her research interests include evolutionary multiobjective optimization and fuzzy systems.
Emerging Networks and Systems Laboratory (ENeS)
Email: [email protected]