3 papers
cs.NE2025
Cascading CMA-ES Instances for Generating Input-diverse Solution Batches
Maria Laura Santoni, Christoph Dürr, Carola Doerr +2
Rather than obtaining a single good solution for a given optimization problem, users often seek alternative design choices, because the best-found solution may perform poorly with…
cs.LG2024
Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization
Maria Laura Santoni, Elena Raponi, Aneta Neumann +3
In real-world applications, users often favor structurally diverse design choices over one high-quality solution. It is hence important to consider more solutions that decision mak…
cs.NE2024
Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization
Konstantin Dietrich, Raphael Patrick Prager, Carola Doerr +1
Exploratory landscape analysis (ELA) is a well-established tool to characterize optimization problems via numerical features. ELA is used for problem comprehension, algorithm desig…