3 papers
cs.NE2026
How Sequential Algorithm Portfolios can benefit Black Box Optimization
Catalin-Viorel Dinu, Diederick Vermetten, Carola Doerr
In typical black-box optimization applications, the available computational budget is often allocated to a single algorithm, typically chosen based on user preference with limited…
cs.NE2025
MECHBench: A Set of Black-Box Optimization Benchmarks originated from Structural Mechanics
Iván Olarte RodrÃguez, Maria Laura Santoni, Fabian Duddeck +3
Benchmarking is essential for developing and evaluating black-box optimization algorithms, providing a structured means to analyze their search behavior. Its effectiveness relies o…
cs.NE2024
MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler
Diederick Vermetten, Jeroen Rook, Oliver L. Preuà +5
Benchmarking is one of the key ways in which we can gain insight into the strengths and weaknesses of optimization algorithms. In sampling-based optimization, considering the anyti…