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33 Publications
2025 | Conference Paper | LibreCat-ID: 56298 | 
R. Gerlach, S. von der Gracht, C. Hahn, J. Harbig, and P. Kling, “Symmetry Preservation in Swarms of Oblivious Robots with Limited Visibility,” in 28th International Conference on Principles of Distributed Systems (OPODIS 2024), Lucca, Italy, 2025, vol. 324, doi: 10.4230/LIPIcs.OPODIS.2024.13.
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| arXiv
2024 | Journal Article | LibreCat-ID: 54548
R. P. Prager and H. Trautmann, “Exploratory Landscape Analysis for Mixed-Variable Problems,” IEEE Transactions on Evolutionary Computation, pp. 1–1, 2024, doi: 10.1109/TEVC.2024.3399560.
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2023 | Conference Paper | LibreCat-ID: 37312 |
D. Leffrang, K. Bösch, and O. Müller, “Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time,” presented at the Hawaii International Conference on System Sciences, 2023.
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2023 | Conference Paper | LibreCat-ID: 50121
D. Leffrang, “AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization,” in International Conference on Information Systems, Hyderabad, India, 2023, no. 10.
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2023 | Conference Paper | LibreCat-ID: 50118
D. Leffrang, “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization,” in Wirtschaftsinformatik Conference, Paderborn, 2023, no. 19.
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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.
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2023 | Book Chapter | LibreCat-ID: 54428
S. Schulte Eickholt, “Normative Diversität? Nahe Zukunft bei Sibylle Berg und Marc-Uwe Kling,” in Germanistik im Wandel 1. Neue Einsichten und Perspektiven in der Literaturwissenschaft, L. Cosan, O. K. Bazarkaya, and H. Tekin, Eds. Berlin: Logos, 2023, pp. 65–75.
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
2020 | Conference Paper | LibreCat-ID: 48897
M. Seiler, J. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem,” in Parallel Problem Solving from {Nature} (PPSN XVI), 2020, pp. 48–64, doi: 10.1007/978-3-030-58112-1_4.
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2020 | Journal Article | LibreCat-ID: 48848
J. Bossek, P. Kerschke, and H. Trautmann, “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms,” Applied Soft Computing, vol. 88, no. C, 2020, doi: 10.1016/j.asoc.2019.105901.
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2020 | Journal Article | LibreCat-ID: 46334
J. Bossek, P. Kerschke, and H. Trautmann, “A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms,” Applied Soft Computing, vol. 88, p. 105901, 2020, doi: https://doi.org/10.1016/j.asoc.2019.105901.
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2019 | Journal Article | LibreCat-ID: 6512 |
G. Rauchecker and G. Schryen, “Using High Performance Computing for Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times: Development and Computational Evaluation of a Parallel Branch-and-Price Algorithm,” Computers & Operations Research, no. 104, pp. 338–357, 2019.
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2019 | Conference Paper | LibreCat-ID: 48875
J. Bossek and H. Trautmann, “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time,” in Learning and Intelligent Optimization, 2019, pp. 215–219, doi: 10.1007/978-3-030-05348-2_19.
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2018 | Conference Paper | LibreCat-ID: 3422
P. Robinson, C. Scheideler, and A. Setzer, “Breaking the $\tilde\Omega(\sqrt{n})$ Barrier: Fast Consensus under a Late Adversary,” in Proceedings of the 30th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), Wien.
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2018 | Conference Paper | LibreCat-ID: 48885
P. Kerschke, J. Bossek, and H. Trautmann, “Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018, pp. 1737–1744, doi: 10.1145/3205651.3208233.
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2018 | Journal Article | LibreCat-ID: 48884
P. Kerschke, L. Kotthoff, J. Bossek, H. H. Hoos, and H. Trautmann, “Leveraging TSP Solver Complementarity through Machine Learning,” Evolutionary Computation, vol. 26, no. 4, pp. 597–620, 2018, doi: 10.1162/evco_a_00215.
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2018 | Conference Paper | LibreCat-ID: 1590
M. Lass, S. Mohr, H. Wiebeler, T. Kühne, and C. Plessl, “A Massively Parallel Algorithm for the Approximate Calculation of Inverse p-th Roots of Large Sparse Matrices,” presented at the Platform for Advanced Scientific Computing Conference (PASC), Basel, Switzerland, 2018, doi: 10.1145/3218176.3218231.
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| arXiv
2017 | Conference Paper | LibreCat-ID: 17652
G. Polevoy, S. Trajanovski, P. Grosso, and C. de Laat, “Filtering Undesirable Flows in Networks,” in Combinatorial Optimization and Applications: 11th International Conference, COCOA 2017, Shanghai, China, December 16-18, 2017, Proceedings, Part I, 2017, pp. 3–17.
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2016 | Conference Paper | LibreCat-ID: 48873
J. Bossek and H. Trautmann, “Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers,” in Learning and Intelligent Optimization, 2016, pp. 48–59, doi: 10.1007/978-3-319-50349-3_4.
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