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197 Publications


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.
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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.
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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.
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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.
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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.
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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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2024 | Conference (Editor) | LibreCat-ID: 58338
M. Affenzeller et al., Eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III, vol. 15150. Springer, 2024.
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2024 | Conference (Editor) | LibreCat-ID: 58336
M. Affenzeller et al., Eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part I, vol. 15148. Springer, 2024.
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2024 | Conference (Editor) | LibreCat-ID: 58339
M. Affenzeller et al., Eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV, vol. 15151. Springer, 2024.
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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.
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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.
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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.
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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.
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2023 | Conference Paper | LibreCat-ID: 48869
J. Bossek, A. Neumann, and F. Neumann, “On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2023, pp. 248–256, doi: 10.1145/3583131.3590384.
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2023 | Conference Paper | LibreCat-ID: 48872
J. Bossek and D. Sudholt, “Runtime Analysis of Quality Diversity Algorithms,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2023, pp. 1546–1554, doi: 10.1145/3583131.3590383.
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2023 | Conference Paper | LibreCat-ID: 48886
A. Marrero, E. Segredo, E. Hart, J. Bossek, and A. Neumann, “Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space,” in Proceedings of the Genetic} and Evolutionary Computation Conference, 2023, pp. 312–320, doi: 10.1145/3583131.3590504.
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2023 | Journal Article | LibreCat-ID: 48871
J. Bossek and D. Sudholt, “Do Additional Target Points Speed Up Evolutionary Algorithms?,” Theoretical Computer Science, p. 113757, 2023, doi: 10.1016/j.tcs.2023.113757.
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2023 | Journal Article | LibreCat-ID: 48859
J. Bossek and C. Grimme, “On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem,” Evolutionary Computation, pp. 1–35, 2023, doi: 10.1162/evco_a_00335.
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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.
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2023 | Conference Paper | LibreCat-ID: 52863
U. Ŝkvorc, T. Eftimov, and P. Koro]ec, “Analyzing the Generalizability of Automated Algorithm Selection: A Case Study for Numerical Optimization,” 2023, doi: 10.1109/ssci52147.2023.10371868.
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