Vinzent Seiler, Moritz, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.”https://doi.org/10.1109/ssci52147.2023.10372008__In 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2024.https://doi.org/10.1109/ssci52147.2023.10372008 .
LibreCat: /record/52749
DOI: 10.1109/ssci52147.2023.10372008

Bossek, Jakob, Aneta Neumann, and Frank Neumann. “On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.”https://doi.org/10.1145/3583131.3590384__In Proceedings of the Genetic and Evolutionary Computation Conference, 248–256. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023.https://doi.org/10.1145/3583131.3590384 .
LibreCat: /record/48869
DOI: 10.1145/3583131.3590384

Bossek, Jakob, and Dirk Sudholt. “Runtime Analysis of Quality Diversity Algorithms.”https://doi.org/10.1145/3583131.3590383__In Proceedings of the Genetic and Evolutionary Computation Conference, 1546–1554. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023.https://doi.org/10.1145/3583131.3590383 .
LibreCat: /record/48872
DOI: 10.1145/3583131.3590383

Marrero, Alejandro, Eduardo Segredo, Emma Hart, Jakob Bossek, and Aneta Neumann. “Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space.”https://doi.org/10.1145/3583131.3590504__In Proceedings of the Genetic and Evolutionary Computation Conference, 312–320. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023.https://doi.org/10.1145/3583131.3590504 .
LibreCat: /record/48886
DOI: 10.1145/3583131.3590504

Bossek, Jakob, and Dirk Sudholt. “Do Additional Target Points Speed Up Evolutionary Algorithms?”https://doi.org/10.1016/j.tcs.2023.113757__Theoretical Computer Science, 2023, 113757.https://doi.org/10.1016/j.tcs.2023.113757 .
LibreCat: /record/48871
DOI: 10.1016/j.tcs.2023.113757

Bossek, Jakob, and Christian Grimme. “On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem.”https://doi.org/10.1162/evco_a_00335__Evolutionary Computation, 2023, 1–35.https://doi.org/10.1162/evco_a_00335 .
LibreCat: /record/48859
DOI: 10.1162/evco_a_00335

Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “A Study on the Effects of Normalized TSP Features for Automated Algorithm Selection.”https://doi.org/10.1016/j.tcs.2022.10.019__Theoretical Computer Science 940 (2023): 123–45.https://doi.org/10.1016/j.tcs.2022.10.019 .
LibreCat: /record/46310
DOI: https://doi.org/10.1016/j.tcs.2022.10.019

Seiler, Moritz Vinzent, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.”https://doi.org/10.1109/SSCI52147.2023.10372008__In 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 361–68, n.d.https://doi.org/10.1109/SSCI52147.2023.10372008 .
LibreCat: /record/48898
DOI: 10.1109/SSCI52147.2023.10372008

Bossek, Jakob, and Frank Neumann. “Exploring the Feature Space of TSP Instances Using Quality Diversity.”https://doi.org/10.1145/3512290.3528851__In Proceedings of the Genetic and Evolutionary Computation Conference, 186–194. GECCO ’22. New York, NY, USA: Association for Computing Machinery, 2022.https://doi.org/10.1145/3512290.3528851 .
LibreCat: /record/48861
DOI: 10.1145/3512290.3528851

Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA.”https://doi.org/10.1145/3520304.3533626__In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 824–842. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022.https://doi.org/10.1145/3520304.3533626 .
LibreCat: /record/48868
DOI: 10.1145/3520304.3533626

Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.”https://doi.org/10.1007/978-3-031-14714-2_14__In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022.https://doi.org/10.1007/978-3-031-14714-2_14 .
LibreCat: /record/48882
DOI: 10.1007/978-3-031-14714-2_14

Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.”https://doi.org/10.1007/978-3-031-14714-2_17__In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\'76 sar, 237–249. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022.https://doi.org/10.1007/978-3-031-14714-2_17 .
LibreCat: /record/48894
DOI: 10.1007/978-3-031-14714-2_17

Clever, Lena, Janina Susanne Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Process-Oriented Stream Classification Pipeline: A Literature Review.”https://doi.org/10.3390/app12189094__Applied Sciences 12, no. 18 (2022): 9094.https://doi.org/10.3390/app12189094 .
LibreCat: /record/48878
DOI: 10.3390/app12189094

Rook, Jeroen, Heike Trautmann, Jakob Bossek, and Christian Grimme. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.”https://doi.org/10.1145/3520304.3528998__In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022.https://doi.org/10.1145/3520304.3528998 .
LibreCat: /record/48896
DOI: 10.1145/3520304.3528998

Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.”https://doi.org/10.1145/3449639.3459364__In Proceedings of the Genetic and Evolutionary Computation Conference, 556–564. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021.https://doi.org/10.1145/3449639.3459364 .
LibreCat: /record/48853
DOI: 10.1145/3449639.3459364

Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Exact Counting And~Sampling of Optima for the Knapsack Problem.”https://doi.org/10.1007/978-3-030-92121-7_4__In Learning and Intelligent Optimization, 40–54. Berlin, Heidelberg: Springer-Verlag, 2021.https://doi.org/10.1007/978-3-030-92121-7_4 .
LibreCat: /record/48855
DOI: 10.1007/978-3-030-92121-7_4

Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.”https://doi.org/10.1145/3449639.3459363__In Proceedings of the Genetic and Evolutionary Computation Conference, 198–206. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021.https://doi.org/10.1145/3449639.3459363 .
LibreCat: /record/48860
DOI: 10.1145/3449639.3459363

Bossek, Jakob, and Dirk Sudholt. “Do Additional Optima Speed up Evolutionary Algorithms?” In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 1–11. New York, NY, USA: Association for Computing Machinery, 2021.
LibreCat: /record/48862

Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal 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, 1–15. New York, NY, USA: Association for Computing Machinery, 2021.
LibreCat: /record/48881

Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.”https://doi.org/10.1145/3449726.3463165__In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1423–1432. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021.https://doi.org/10.1145/3449726.3463165 .
LibreCat: /record/48876
DOI: 10.1145/3449726.3463165