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153 Publications
2025 | Journal Article | LibreCat-ID: 59073
Rook, J. G., Benjamins, C., Bossek, J., Trautmann, H., Hoos, H. H., & Lindauer, M. (2025). MO-SMAC: Multi-objective Sequential Model-based Algorithm Configuration. Evolutionary Computation, 1–25. https://doi.org/10.1162/evco_a_00371
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2025 | Conference Paper | LibreCat-ID: 60219
Vermetten, D., Rook, J., Preuß, O. L., de Nobel, J., Doerr, C., López-Ibáñez, M., Trautmann, H., & Bäck, T. (2025). MO-IOHinspector: Anytime Benchmarking of Multi-objective Algorithms Using IOHprofiler. In H. K. Singh, T. Ray, J. D. Knowles, X. Li, J. Branke, B. Wang, & A. Oyama (Eds.), Evolutionary Multi-Criterion Optimization - 13th International Conference, EMO 2025, Canberra, ACT, Australia, March 4-7, 2025, Proceedings, Part I (Vol. 15512, pp. 242–256). Springer. https://doi.org/10.1007/978-981-96-3506-1_17
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2025 | Journal Article | LibreCat-ID: 60220
Seiler, M., Kerschke, P., & Trautmann, H. (2025). Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems . Evolutionary Computation, 1–27. https://doi.org/10.1162/evco_a_00367
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2025 | Conference Paper | LibreCat-ID: 60813
Seiler, M., Preuß, O. L., & Trautmann, H. (2025). RandOptGen: A Unified Random Problem Generator for Single- and Multi-Objective Optimization Problems with Mixed-Variable Input Spaces. In B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025 (pp. 76–84). ACM. https://doi.org/10.1145/3712256.3726478
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2025 | Conference Paper | LibreCat-ID: 60812
Preuß, O. L., Mensendiek, C., Rook, J., Bossek, J., & Trautmann, H. (2025). Automated Algorithm Configuration and Systematic Benchmarking for Heterogeneous MNK-Landscapes. In B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025 (pp. 58–66). ACM. https://doi.org/10.1145/3712256.3726481
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2025 | Conference Paper | LibreCat-ID: 60814
Schede, E., Seiler, M., Tierney, K., & Trautmann, H. (2025). Deep reinforcement learning for instance-specific algorithm configuration (GECCO Best Paper Award). In B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025 (pp. 1190–1198). ACM. https://doi.org/10.1145/3712256.3726480
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2025 | Conference Paper | LibreCat-ID: 61032
Rodriguez-Fernandez, A. E., Schäpermeier, L., Castellanos, C. H., Kerschke, P., Trautmann, H., & Schütze, O. (2025). Hot off the Press: Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025, 61–62. https://doi.org//10.1145/3712255.3734260
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2025 | Conference Paper | LibreCat-ID: 61918
Rook, J., Renau, Q., Trautmann, H., & Hart, E. (2025). Efficient Online Automated Algorithm Selection in the Face of Data-Drift in Optimisation Problem Instances. Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2025, Leiden, The Netherlands, August 27-29, 2025, 262–272. https://doi.org/10.1145/3729878.3746615
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2025 | Journal Article | LibreCat-ID: 63053
Hernández, C., Rodriguez-Fernandez, A. E., Schäpermeier, L., Cuate, O., Trautmann, H., & Schütze, O. (2025). An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary Computation, 1–1. https://doi.org/10.1109/TEVC.2025.3637276
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2025 | Report | LibreCat-ID: 63633
Eimer, T., Schäpermeier, L., Biedenkapp, A., Tornede, A., Kotthoff, L., Leyman, P., Feurer, M., Eggensperger, K., Maile, K., Tornede, T., Kozak, A., Xue, K., Wever, M. D., Baratchi, M., Pulatov, D., Trautmann, H., Kashgarani, H., & Lindauer, M. (2025). Best Practices For Empirical Meta-Algorithmic Research: Guidelines from the COSEAL Research Network. https://doi.org/DOI:10.48550/arXiv.2512.16491
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2024 | Journal Article | LibreCat-ID: 54548
Prager, R. P., & Trautmann, H. (2024). Exploratory Landscape Analysis for Mixed-Variable Problems. IEEE Transactions on Evolutionary Computation, 1–1. https://doi.org/10.1109/TEVC.2024.3399560
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2024 | Conference Paper | LibreCat-ID: 54642
Dietrich, K., Prager, R., Doerr, C., & Trautmann, H. (2024). Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization. In M. Affenzeller, S. Winkler, A. Kononova, H. Trautmann, T. Tušar, P. Machado, & T. Baeck (Eds.), Parallel Problem Solving from Nature — PPSN XVIII (pp. 1–14). Springer International Publishing.
LibreCat
2024 | Conference Paper | LibreCat-ID: 54643
Seiler, M., Skvorc, U., Cenikj, G., Doerr, C., & Trautmann, H. (2024). Learned Features vs. Classical ELA on Affine BBOB Functions. In M. Affenzeller, S. Winkler, A. Kononova, H. Trautmann, T. Tušar, P. Machado, & T. Baeck (Eds.), Parallel Problem Solving from Nature — PPSN XVIII (pp. 1–14). Springer International Publishing.
LibreCat
2024 | Book Chapter | LibreCat-ID: 52759
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. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56852-7_20
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2024 | Conference Paper | LibreCat-ID: 52749
Seiler, M., Rook, J., Heins, J., Preuß, O. L., Bossek, J., & Trautmann, H. (2024). Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. 2023 IEEE Symposium Series on Computational Intelligence (SSCI). https://doi.org/10.1109/ssci52147.2023.10372008
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2024 | Conference Paper | LibreCat-ID: 55649
Rook, J., Hoos, H. H., & Trautmann, H. (2024). Multi-objective Ranking using Bootstrap Resampling. In X. Li & J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 (pp. 155–158). ACM. https://doi.org/10.1145/3638530.3654436
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2024 | Journal Article | LibreCat-ID: 56221
Rodriguez-Fernandez, A. E., Schäpermeier, L., Hernández, C., Kerschke, P., Trautmann, H., & Schütze, O. (2024). Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary Computation, 1–1. https://doi.org/10.1109/TEVC.2024.3458855
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2024 | Conference Paper | LibreCat-ID: 58335
Seiler, M., Skvorc, U., Doerr, C., & Trautmann, H. (2024). Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection. In P. Festa, D. Ferone, T. Pastore, & O. Pisacane (Eds.), Learning and Intelligent Optimization - 18th International Conference, LION 18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers (Vol. 14990, pp. 361–376). Springer. https://doi.org/10.1007/978-3-031-75623-8_29
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2024 | Conference (Editor) | LibreCat-ID: 58338
Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T., Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III (Vol. 15150). Springer. https://doi.org/10.1007/978-3-031-70071-2
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2024 | Conference (Editor) | LibreCat-ID: 58336
Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T., Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part I (Vol. 15148). Springer. https://doi.org/10.1007/978-3-031-70055-2
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