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10 Publications
2023 | Journal Article | LibreCat-ID: 46310
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.” Theoretical Computer Science 940 (2023): 123–45. https://doi.org/10.1016/j.tcs.2022.10.019.
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2021 | Book Chapter | LibreCat-ID: 48881
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
2020 | Journal Article | LibreCat-ID: 46334
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing 88 (2020): 105901. https://doi.org/10.1016/j.asoc.2019.105901.
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2020 | Conference Paper | LibreCat-ID: 48897
Seiler, Moritz, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike 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), 48–64. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_4.
LibreCat
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2020 | Journal Article | LibreCat-ID: 48848
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing 88, no. C (2020). https://doi.org/10.1016/j.asoc.2019.105901.
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2019 | Conference Paper | LibreCat-ID: 48875
Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” In Learning and Intelligent Optimization, edited by Roberto Battiti, Mauro Brunato, Ilias Kotsireas, and Panos M. Pardalos, 215–219. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-05348-2_19.
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2018 | Conference Paper | LibreCat-ID: 48885
Kerschke, Pascal, Jakob Bossek, and Heike 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, 1737–1744. GECCO’18. New York, NY, USA: Association for Computing Machinery, 2018. https://doi.org/10.1145/3205651.3208233.
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2018 | Journal Article | LibreCat-ID: 48884
Kerschke, Pascal, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, and Heike Trautmann. “Leveraging TSP Solver Complementarity through Machine Learning.” Evolutionary Computation 26, no. 4 (2018): 597–620. https://doi.org/10.1162/evco_a_00215.
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2016 | Conference Paper | LibreCat-ID: 48873
Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers.” In Learning and Intelligent Optimization, edited by Paola Festa, Meinolf Sellmann, and Joaquin Vanschoren, 48–59. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-50349-3_4.
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2012 | Conference Paper | LibreCat-ID: 46396
Bischl, Bernd, Olaf Mersmann, Heike Trautmann, and Mike Preuß. “Algorithm Selection Based on Exploratory Landscape Analysis and Cost-Sensitive Learning.” In Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, 313–320. GECCO ’12. New York, NY, USA: Association for Computing Machinery, 2012. https://doi.org/10.1145/2330163.2330209.
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