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191 Publications
2024 | Conference Paper | LibreCat-ID: 52749
M. Vinzent 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
| DOI
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
| DOI
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
| DOI
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.
LibreCat
| DOI
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.
LibreCat
| DOI
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.
LibreCat
| DOI
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
| DOI
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 | 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.
LibreCat
| DOI
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.
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
| DOI
2023 | Conference Paper | LibreCat-ID: 48898
M. V. Seiler, J. Rook, J. Heins, O. L. Preuß, J. Bossek, and H. Trautmann, “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP,” in 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 361–368, doi: 10.1109/SSCI52147.2023.10372008.
LibreCat
| DOI
2022 | Journal Article | LibreCat-ID: 46316
D. Assenmacher et al., “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem,” Social Science Computer Review, vol. 40, no. 6, pp. 1496–1522, 2022, doi: 10.1177/08944393211012268.
LibreCat
| DOI
2022 | Journal Article | LibreCat-ID: 46309
L. Clever, J. S. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Process-Oriented Stream Classification Pipeline: A Literature Review,” Applied Sciences, vol. 12, no. 8, pp. 1–44, 2022, doi: 10.3390/app12189094.
LibreCat
| DOI
2022 | Journal Article | LibreCat-ID: 46308
P. Aspar, V. Steinhoff, L. Schäpermeier, P. Kerschke, H. Trautmann, and C. Grimme, “The objective that freed me: a multi-objective local search approach for continuous single-objective optimization,” Natural Computing, vol. 1, pp. 1–15, 2022, doi: 10.1007/s11047-022-09919-w.
LibreCat
| DOI
2022 | Journal Article | LibreCat-ID: 48878
L. Clever, J. S. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Process-Oriented Stream Classification Pipeline: A Literature Review,” Applied Sciences, vol. 12, no. 18, p. 9094, 2022, doi: 10.3390/app12189094.
LibreCat
| DOI
2022 | Journal Article | LibreCat-ID: 52532
A. S. Rodrigues et al., “Estimation of component reliability from superposed renewal processes by means of latent variables,” Comput. Stat., vol. 37, no. 1, pp. 355–379, 2022, doi: 10.1007/S00180-021-01124-0.
LibreCat
| DOI
2022 | Conference Paper | LibreCat-ID: 46301
D. Assenmacher and H. Trautmann, “Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption,” in Intelligent Information and Database Systems, 2022, pp. 3–16, doi: 10.1007/978-3-031-21743-2_1.
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