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64 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.
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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.
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.
LibreCat
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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
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2022 | Conference Paper | LibreCat-ID: 48861
J. Bossek and F. Neumann, “Exploring the Feature Space of TSP Instances Using Quality Diversity,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2022, pp. 186–194, doi: 10.1145/3512290.3528851.
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2022 | Conference Paper | LibreCat-ID: 48868
J. Bossek, A. Neumann, and F. Neumann, “Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, pp. 824–842, doi: 10.1145/3520304.3533626.
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2022 | Conference Paper | LibreCat-ID: 48882
J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann, “BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,” in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 192–206, doi: 10.1007/978-3-031-14714-2_14.
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2022 | Conference Paper | LibreCat-ID: 48894
A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem,” in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 237–249, doi: 10.1007/978-3-031-14714-2_17.
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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.
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2022 | Conference Paper | LibreCat-ID: 48896
J. Rook, H. Trautmann, J. Bossek, and C. Grimme, “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, pp. 356–359, doi: 10.1145/3520304.3528998.
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2021 | Conference Paper | LibreCat-ID: 48853
J. Bossek, A. Neumann, and F. Neumann, “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2021, pp. 556–564, doi: 10.1145/3449639.3459364.
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2021 | Conference Paper | LibreCat-ID: 48855
J. Bossek, A. Neumann, and F. Neumann, “Exact Counting and~Sampling of Optima for the Knapsack Problem,” in Learning and Intelligent Optimization, 2021, pp. 40–54, doi: 10.1007/978-3-030-92121-7_4.
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2021 | Conference Paper | LibreCat-ID: 48860
J. Bossek and F. Neumann, “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2021, pp. 198–206, doi: 10.1145/3449639.3459363.
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2021 | Book Chapter | LibreCat-ID: 48862
J. Bossek and D. Sudholt, “Do Additional Optima Speed up Evolutionary Algorithms?,” in Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–11.
LibreCat
2021 | Book Chapter | LibreCat-ID: 48881
J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, and P. Kerschke, “On the Potential of Normalized TSP Features for Automated Algorithm Selection,” in Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–15.
LibreCat
2021 | Conference Paper | LibreCat-ID: 48876
J. Bossek and M. Wagner, “Generating Instances with Performance Differences for More than Just Two Algorithms,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021, pp. 1423–1432, doi: 10.1145/3449726.3463165.
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