Advanced methodology of evolutionary multi- and many-objective optimization for real-world applications
B. Filipič, T. Tušar, E. Dovgan, J. Zupančič
The goal of this collaboration between Japanese and Slovenian researchers was to advance the methodology of evolutionary multi- and many-objective optimization for real-world applications. It considered three important topics: (1) state-of-the-art evolutionary algorithms design and development, (2) surrogate models and visualization tools, and (3) real-world applications. Unlike most other research efforts, our research unified these approaches to effectively tackle the problems observed in complex application domains that are multi- and many-objective, computationally expensive, require surrogate models, and benefit from domain knowledge. The focus of the joint research was on optimization and visualization in many-objective space trajectory design.