BDA @ EMO 2023

Between the 20th and 24th of March, Pascal Kerschke and Lennart Schäpermeier from the chair of Big Data Analytics in Transportation successfully participated in the 12th Evolutionary Multi-criterion Optimization (EMO) conference in Leiden, The Netherlands. Next to attending inspiring keynotes, tutorials, and presentations of the conference contributions by other researchers, they actively contributed a tutorial and a research paper.

For the tutorial, titled "Continuous Multimodal Multi-objective Optimization," they were joined by their colleague Christian Grimme from the University of Münster. Next to theoretical underpinnings and an overview of the research landscape, the tutorial focused on visualization techniques and their utilization to analyze properties of common benchmark problems in multi-objective optimization. Their key tool for visualizing the problems is the visualization dashboard at https://schaepermeier.shinyapps.io/moPLOT.

Then, in their presentation to the paper titled "Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets" [1], they introduced a methodology to create well-understood multimodal benchmark problems with more diverse characteristics than the widespread benchmark sets. The paper is co-authored with their colleagues Christian Grimme and Heike Trautmann, one of the conference's keynote speakers, from the University of Münster.

[1] Schäpermeier, L., Kerschke, P., Grimme, C., Trautmann, H. (2023). Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets. In: Evolutionary Multi-Criterion Optimization. EMO 2023. Lecture Notes in Computer Science, vol 13970. Springer, Cham. https://doi.org/10.1007/978-3-031-27250-9_21