Tutorials

Dr. Hamada Naoki

Senior Researcher, Artificial Intelligence Laboratory
Fujitsu Laboratories Ltd., Japan

Title: Evolutionary Multi-objective Optimization and Topological Data Analysis for Designing Innovative Products

Abstract:
Evolutionary Computation (EC) and Machine Learning (ML) are excellent tools to model, analyze and optimize various kinds of industrial problems. Since real-world problems often involve conflicting objectives to be optimized (e.g., cost vs. performance), we need to consider a trade-off between objectives. While such a trade-off surface can be obtained by using Evolutionary Multi-objective Optimization (EMO) algorithms, the dimensionality of the surface becomes higher as the number of objectives grows. Thus after optimization, additional analysis and visualization are required for understanding the trade-off. This talk introduces an emerging ML technique to analyze EMO outcomes: Topological Data Analysis (TDA), originated from...