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39 Publications
2023 | Conference Paper | LibreCat-ID: 33490
Rieskamp J, Hofeditz L, Mirbabaie M, Stieglitz S. Approaches to Improve Fairness when Deploying AI-based Algorithms in Hiring – Using a Systematic Literature Review to Guide Future Research. In: Proceedings of the Annual Hawaii International Conference on System Sciences (HICSS). ; 2023.
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2023 | Conference Paper | LibreCat-ID: 48869
Bossek J, Neumann A, Neumann F. 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. GECCO’23. Association for Computing Machinery; 2023:248–256. doi:10.1145/3583131.3590384
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2023 | Journal Article | LibreCat-ID: 48871
Bossek J, Sudholt D. Do Additional Target Points Speed Up Evolutionary Algorithms? Theoretical Computer Science. Published online 2023:113757. doi:10.1016/j.tcs.2023.113757
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2023 | Report | LibreCat-ID: 52127
Moura L, Nakic A, Östergård P, Wassermann A, Weiß C. Pushing the Limits of Computational Combinatorial Constructions (Dagstuhl Seminar 23161). Vol 13, Issue 4. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023:40-57. doi:10.4230/DagRep.13.4.40
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2022 | Conference Paper | LibreCat-ID: 48894
Nikfarjam A, Neumann A, Bossek J, Neumann F. Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tu\v sar T, eds. Parallel Problem Solving from Nature (PPSN XVII). Lecture Notes in Computer Science. Springer International Publishing; 2022:237–249. doi:10.1007/978-3-031-14714-2_17
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2021 | Journal Article | LibreCat-ID: 22510
Li S, Markarian C, Meyer auf der Heide F, Podlipyan P. A continuous strategy for collisionless gathering. Theoretical Computer Science. 2021;852:41-60. doi:10.1016/j.tcs.2020.10.037
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2021 | Journal Article | LibreCat-ID: 22511
Li S, Meyer auf der Heide F, Podlipyan P. The impact of the Gabriel subgraph of the visibility graph on the gathering of mobile autonomous robots. Theoretical Computer Science. 2021;852:29-40. doi:10.1016/j.tcs.2020.11.009
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2021 | Journal Article | LibreCat-ID: 46318
Grimme C, Kerschke P, Aspar P, et al. Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research. 2021;136:105489. doi:https://doi.org/10.1016/j.cor.2021.105489
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2021 | Conference Paper | LibreCat-ID: 48853
Bossek J, Neumann A, Neumann F. Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’21. Association for Computing Machinery; 2021:556–564. doi:10.1145/3449639.3459364
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2021 | Conference Paper | LibreCat-ID: 48860
Bossek J, Neumann F. Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’21. Association for Computing Machinery; 2021:198–206. doi:10.1145/3449639.3459363
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2021 | Book Chapter | LibreCat-ID: 48862
Bossek J, Sudholt D. Do Additional Optima Speed up Evolutionary Algorithms? In: Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. Association for Computing Machinery; 2021:1–11.
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2021 | Conference Paper | LibreCat-ID: 48876
Bossek J, Wagner M. Generating Instances with Performance Differences for More than Just Two Algorithms. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO’21. Association for Computing Machinery; 2021:1423–1432. doi:10.1145/3449726.3463165
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2021 | Conference Paper | LibreCat-ID: 48893
Nikfarjam A, Bossek J, Neumann A, Neumann F. Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO’21. Association for Computing Machinery; 2021:600–608. doi:10.1145/3449639.3459384
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2021 | Conference Paper | LibreCat-ID: 48891
Neumann A, Bossek J, Neumann F. Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO’21. Association for Computing Machinery; 2021:261–269. doi:10.1145/3449639.3459385
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2021 | Book Chapter | LibreCat-ID: 48892
Nikfarjam A, Bossek J, Neumann A, Neumann F. 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. Association for Computing Machinery; 2021:1–11.
LibreCat
2021 | Journal Article | LibreCat-ID: 48854
Bossek J, Neumann F, Peng P, Sudholt D. Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. Algorithmica. 2021;83(10):3148–3179. doi:10.1007/s00453-021-00838-3
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2020 | Conference Paper | LibreCat-ID: 48847
Bossek J, Neumann F, Peng P, Sudholt D. More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’20. Association for Computing Machinery; 2020:1277–1285. doi:10.1145/3377930.3390174
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2020 | Conference Paper | LibreCat-ID: 48851
Bossek J, Casel K, Kerschke P, Neumann F. The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’20. Association for Computing Machinery; 2020:1286–1294. doi:10.1145/3377930.3390243
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2020 | Conference Paper | LibreCat-ID: 48845
Bossek J, Grimme C, Trautmann H. Dynamic Bi-Objective Routing of Multiple Vehicles. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’20. Association for Computing Machinery; 2020:166–174. doi:10.1145/3377930.3390146
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2020 | Conference Paper | LibreCat-ID: 48852
Bossek J, Neumann A, Neumann F. Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions. In: Parallel Problem Solving from Nature (PPSN XVI). Springer-Verlag; 2020:346–359. doi:10.1007/978-3-030-58112-1_24
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