20 citations · 29 across the 7 of their papers we have counts for
5 papers · 1 filter
MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler
Diederick Vermetten, Jeroen Rook, Oliver L. Preuß +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…
Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler
Diederick Vermetten, Johannes Lengler, Dimitri Rusin +2
Optimization problems in dynamic environments have recently been the source of several theoretical studies. One of these problems is the monotonic Dynamic Binary Value problem, whi…
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization
Konstantin Dietrich, Diederick Vermetten, Carola Doerr +1
The recently proposed MA-BBOB function generator provides a way to create numerical black-box benchmark problems based on the well-established BBOB suite. Initial studies on this g…
Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms
Manuel López-Ibáñez, Diederick Vermetten, Johann Dreo +1
A widely accepted way to assess the performance of iterative black-box optimizers is to analyze their empirical cumulative distribution function (ECDF) of pre-defined quality targe…
Large-scale Benchmarking of Metaphor-based Optimization Heuristics
Diederick Vermetten, Carola Doerr, Hao Wang +2
The number of proposed iterative optimization heuristics is growing steadily, and with this growth, there have been many points of discussion within the wider community. One partic…