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142 Publications
2025 | Journal Article | LibreCat-ID: 59073
J. G. Rook, C. Benjamins, J. Bossek, H. Trautmann, H. H. Hoos, and M. Lindauer, “MO-SMAC: Multi-objective Sequential Model-based Algorithm Configuration,” Evolutionary Computation, pp. 1–25, 2025, doi: 10.1162/evco_a_00371.
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 54548
R. P. Prager and H. Trautmann, “Exploratory Landscape Analysis for Mixed-Variable Problems,” IEEE Transactions on Evolutionary Computation, pp. 1–1, 2024, doi: 10.1109/TEVC.2024.3399560.
LibreCat
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2024 | Conference Paper | LibreCat-ID: 54642
K. Dietrich, R. Prager, C. Doerr, and H. Trautmann, “Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization,” in Parallel Problem Solving from Nature — PPSN XVIII, 2024, pp. 1–14.
LibreCat
2024 | Conference Paper | LibreCat-ID: 54643
M. Seiler, U. Skvorc, G. Cenikj, C. Doerr, and H. Trautmann, “Learned Features vs. Classical ELA on Affine BBOB Functions,” in Parallel Problem Solving from Nature — PPSN XVIII, 2024, pp. 1–14.
LibreCat
2024 | Book Chapter | LibreCat-ID: 52759
O. L. Preuß, J. Rook, and H. Trautmann, “On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems,” in Applications of Evolutionary Computation, Cham: Springer Nature Switzerland, 2024.
LibreCat
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2024 | Conference Paper | LibreCat-ID: 52749
M. Seiler, J. Rook, J. Heins, O. L. Preuß, J. Bossek, and H. Trautmann, “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP,” 2024, doi: 10.1109/ssci52147.2023.10372008.
LibreCat
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2024 | Conference Paper | LibreCat-ID: 55649
J. Rook, H. H. Hoos, and H. Trautmann, “Multi-objective Ranking using Bootstrap Resampling,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024, 2024, pp. 155–158, doi: 10.1145/3638530.3654436.
LibreCat
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2024 | Journal Article | LibreCat-ID: 56221
A. E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann, and O. Schütze, “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization,” IEEE Transactions on Evolutionary Computation, pp. 1–1, 2024, doi: 10.1109/TEVC.2024.3458855.
LibreCat
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2024 | Conference Paper | LibreCat-ID: 58335
M. Seiler, U. Skvorc, C. Doerr, and H. Trautmann, “Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection,” in Learning and Intelligent Optimization - 18th International Conference, LION 18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers, 2024, vol. 14990, pp. 361–376, doi: 10.1007/978-3-031-75623-8_29.
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2023 | Conference Paper | LibreCat-ID: 47522
R. P. Prager et al., “Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features,” in Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023, pp. 129–139, doi: 10.1145/3594805.3607136.
LibreCat
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2023 | Conference Paper | LibreCat-ID: 46297
R. P. Prager and H. Trautmann, “Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features,” in Applications of Evolutionary Computation, 2023, pp. 411–425.
LibreCat
2023 | Conference Paper | LibreCat-ID: 46298
L. Schäpermeier, P. Kerschke, C. Grimme, and H. Trautmann, “Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets,” in Evolutionary Multi-Criterion Optimization, 2023, pp. 291–304.
LibreCat
2023 | Journal Article | LibreCat-ID: 46299
R. P. Prager and H. Trautmann, “Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python,” Evolutionary Computation, pp. 1–25, 2023, doi: 10.1162/evco_a_00341.
LibreCat
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2023 | Conference Paper | LibreCat-ID: 52530
R. P. Prager and H. Trautmann, “Investigating the Viability of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems,” in Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023, 2023, pp. 451–454, doi: 10.1145/3583133.3590757.
LibreCat
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2023 | Journal Article | LibreCat-ID: 46310
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, and P. Kerschke, “A study on the effects of normalized TSP features for automated algorithm selection,” Theoretical Computer Science, vol. 940, pp. 123–145, 2023, doi: https://doi.org/10.1016/j.tcs.2022.10.019.
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