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40 Publications
2024 | Journal Article | LibreCat-ID: 56221
A. E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann, and O. Schütze, “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization,” IEEE Transactions on Evolutionary Computation, pp. 1–1, 2024, doi: 10.1109/TEVC.2024.3458855.
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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 | 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 | Conference Paper | LibreCat-ID: 33490
J. Rieskamp, L. Hofeditz, M. Mirbabaie, and S. Stieglitz, “Approaches to Improve Fairness when Deploying AI-based Algorithms in Hiring – Using a Systematic Literature Review to Guide Future Research,” presented at the Proceedings of the Annual Hawaii International Conference on System Sciences (HICSS), 2023.
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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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2021 | Journal Article | LibreCat-ID: 46318
C. Grimme et al., “Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization,” Computers & Operations Research, vol. 136, p. 105489, 2021, doi: https://doi.org/10.1016/j.cor.2021.105489.
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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: 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 | 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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2021 | Conference Paper | LibreCat-ID: 48893
A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2021, pp. 600–608, doi: 10.1145/3449639.3459384.
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2021 | Conference Paper | LibreCat-ID: 48891
A. Neumann, J. Bossek, and F. Neumann, “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2021, pp. 261–269, doi: 10.1145/3449639.3459385.
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2021 | Book Chapter | LibreCat-ID: 48892
A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation,” 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 | Journal Article | LibreCat-ID: 48854
J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem,” Algorithmica, vol. 83, no. 10, pp. 3148–3179, 2021, doi: 10.1007/s00453-021-00838-3.
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2020 | Conference Paper | LibreCat-ID: 48847
J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 1277–1285, doi: 10.1145/3377930.3390174.
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2020 | Conference Paper | LibreCat-ID: 48851
J. Bossek, K. Casel, P. Kerschke, and F. Neumann, “The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 1286–1294, doi: 10.1145/3377930.3390243.
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2020 | Conference Paper | LibreCat-ID: 48845
J. Bossek, C. Grimme, and H. Trautmann, “Dynamic Bi-Objective Routing of Multiple Vehicles,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 166–174, doi: 10.1145/3377930.3390146.
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