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64 Publications
2024 | Conference Paper | LibreCat-ID: 52749
Vinzent Seiler, Moritz, et al. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.” 2023 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2024, doi:10.1109/ssci52147.2023.10372008.
LibreCat
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2023 | Conference Paper | LibreCat-ID: 48869
Bossek, Jakob, et al. “On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2023, pp. 248–256, doi:10.1145/3583131.3590384.
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2023 | Conference Paper | LibreCat-ID: 48872
Bossek, Jakob, and Dirk Sudholt. “Runtime Analysis of Quality Diversity Algorithms.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2023, pp. 1546–1554, doi:10.1145/3583131.3590383.
LibreCat
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2023 | Conference Paper | LibreCat-ID: 48886
Marrero, Alejandro, et al. “Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space.” Proceedings of the Genetic} and Evolutionary Computation Conference, Association for Computing Machinery, 2023, pp. 312–320, doi:10.1145/3583131.3590504.
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2023 | Journal Article | LibreCat-ID: 48871
Bossek, Jakob, and Dirk Sudholt. “Do Additional Target Points Speed Up Evolutionary Algorithms?” Theoretical Computer Science, 2023, p. 113757, doi:10.1016/j.tcs.2023.113757.
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2023 | Journal Article | LibreCat-ID: 48859
Bossek, Jakob, and Christian Grimme. “On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem.” Evolutionary Computation, 2023, pp. 1–35, doi:10.1162/evco_a_00335.
LibreCat
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2023 | Journal Article | LibreCat-ID: 46310
Heins, Jonathan, et al. “A Study on the Effects of Normalized TSP Features for Automated Algorithm Selection.” Theoretical Computer Science, vol. 940, 2023, pp. 123–45, doi:https://doi.org/10.1016/j.tcs.2022.10.019.
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2023 | Conference Paper | LibreCat-ID: 48898
Seiler, Moritz Vinzent, et al. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.” 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 361–68, doi:10.1109/SSCI52147.2023.10372008.
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2022 | Conference Paper | LibreCat-ID: 48861
Bossek, Jakob, and Frank Neumann. “Exploring the Feature Space of TSP Instances Using Quality Diversity.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2022, pp. 186–194, doi:10.1145/3512290.3528851.
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2022 | Conference Paper | LibreCat-ID: 48868
Bossek, Jakob, et al. “Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2022, pp. 824–842, doi:10.1145/3520304.3533626.
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2022 | Conference Paper | LibreCat-ID: 48882
Heins, Jonathan, et al. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 192–206, doi:10.1007/978-3-031-14714-2_14.
LibreCat
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2022 | Conference Paper | LibreCat-ID: 48894
Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249, doi:10.1007/978-3-031-14714-2_17.
LibreCat
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2022 | Journal Article | LibreCat-ID: 48878
Clever, Lena, et al. “Process-Oriented Stream Classification Pipeline: A Literature Review.” Applied Sciences, vol. 12, no. 18, {Multidisciplinary Digital Publishing Institute}, 2022, p. 9094, doi:10.3390/app12189094.
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2022 | Conference Paper | LibreCat-ID: 48896
Rook, Jeroen, et al. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2022, pp. 356–359, doi:10.1145/3520304.3528998.
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2021 | Conference Paper | LibreCat-ID: 48853
Bossek, Jakob, et al. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2021, pp. 556–564, doi:10.1145/3449639.3459364.
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2021 | Conference Paper | LibreCat-ID: 48855
Bossek, Jakob, et al. “Exact Counting And~Sampling of Optima for the Knapsack Problem.” Learning and Intelligent Optimization, Springer-Verlag, 2021, pp. 40–54, doi:10.1007/978-3-030-92121-7_4.
LibreCat
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2021 | Conference Paper | LibreCat-ID: 48860
Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2021, pp. 198–206, doi:10.1145/3449639.3459363.
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2021 | Book Chapter | LibreCat-ID: 48862
Bossek, Jakob, and Dirk Sudholt. “Do Additional Optima Speed up Evolutionary Algorithms?” Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, 2021, pp. 1–11.
LibreCat
2021 | Book Chapter | LibreCat-ID: 48881
Heins, Jonathan, et al. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, 2021, pp. 1–15.
LibreCat
2021 | Conference Paper | LibreCat-ID: 48876
Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2021, pp. 1423–1432, doi:10.1145/3449726.3463165.
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