IOHprofiler: A benchmarking and profiling tool for iterative optimization heuristics C Doerr, H Wang, F Ye, S van Rijn, T Bäck arXiv preprint arXiv:1810.05281, 2018 | 41 | 2018 |
Evolving the structure of Evolution Strategies S van Rijn, H Wang, M van Leeuwen, T Bäck Computational Intelligence (SSCI), 2016 IEEE Symposium Series on, 1-8, 2016 | 38 | 2016 |
Online selection of CMA-ES variants D Vermetten, S van Rijn, T Bäck, C Doerr Proceedings of the Genetic and Evolutionary Computation Conference, 951-959, 2019 | 20 | 2019 |
Algorithm configuration data mining for CMA evolution strategies S van Rijn, H Wang, B van Stein, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference, 737-744, 2017 | 20 | 2017 |
Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1+ λ) EA variants on onemax and leadingones C Doerr, F Ye, S van Rijn, H Wang, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference, 951-958, 2018 | 16 | 2018 |
Optimizing highly constrained truck loadings using a self-adaptive genetic algorithm S van Rijn, M Emmerich, E Reehuis, T Bäck 2015 IEEE Congress on Evolutionary Computation (CEC), 227-234, 2015 | 15 | 2015 |
Towards an Adaptive CMA-ES Configurator S van Rijn, C Doerr, T Bäck International Conference on Parallel Problem Solving from Nature, 54-65, 2018 | 11 | 2018 |
Multi-fidelity surrogate model approach to optimization S van Rijn, S Schmitt, M Olhofer, M van Leeuwen, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018 | 5 | 2018 |
IOHprofiler: a benchmarking and profiling tool for iterative optimization heuristics. arXiv e-prints: 1810.05281, October 2018 C Doerr, H Wang, F Ye, S van Rijn, T Bäck URL https://arxiv. org/abs, 1810 | 5 | 1810 |
MF2: A Collection of Multi-Fidelity Benchmark Functions in Python S van Rijn, S Schmitt Journal of Open Source Software 5 (52), 2049, 2020 | 1 | 2020 |
Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling S van Rijn, S Schmitt, M van Leeuwen, T Bäck arXiv preprint arXiv:2103.03280, 2021 | | 2021 |