J.G. Rook MSc (Jeroen)



Engineering & Materials Science
Multiobjective Optimization
Computational Science
Performance Comparison


Preuß, O. L. , Rook, J. , & Trautmann, H. (2024). On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems. In Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part I (pp. 305-321). (Lecture Notes in Computer Science; Vol. 14634). https://doi.org/10.1007/978-3-031-56852-7_20
Seiler, M. V. , Rook, J., Heins, J., Preuß, O. L., Bossek, J. , & Trautmann, H. (2023). Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 361-368). (IEEE Symposium Series on Computational Intelligence; Vol. 2023). IEEE. https://doi.org/10.1109/SSCI52147.2023.10372008
Leszkiewicz, A. , Bucur, D., Grimme, C., Michalski, R., Clever, L., Pohl, J. , Rook, J., Bossek, J., Preuss, M., Squillero, G., Quer, S., Calabrese, A., Iacca, G. , Kizgin, D. H. , & Trautmann, H. (2022). Social Influence Analysis (SIA) in Online Social Networks. Paper presented at 4th Multidisciplinary International Symposium, MISDOOM 2022 , Boise, Idaho, United States.
van der Blom, K., Hoos, H., Luo, C. , & Rook, J. (2022). Sparkle: Towards Accessible Meta-Algorithmics for Improving the State of the Art in Solving Challenging Problems. IEEE Transactions on Evolutionary Computation, 26(6), 1351-1364. https://doi.org/10.1109/TEVC.2022.3215013
Heins, J. , Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J. , & Trautmann, H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature: PPSN XVII (pp. 192-206). (Lecture Notes in Computer Science; Vol. 13398). Springer. https://doi.org/10.1007/978-3-031-14714-2_14
Rook, J. , Trautmann, H., Bossek, J., & Grimme, C. (2022). On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems. In GECCO 2022 Companion: Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 356-359). Association for Computing Machinery. https://doi.org/10.1145/3520304.3528998, https://doi.org/10.1145/3520304.3528998

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Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (gebouwnr. 11), kamer 4126
Hallenweg 19
7522NH  Enschede

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Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling  4126
Postbus 217
7500 AE Enschede