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10 Publications
2023 | Journal Article | LibreCat-ID: 46310
Heins, Jonathan, et al. “A Study on the Effects of Normalized TSP Features for Automated Algorithm Selection.” Theoretical Computer Science, vol. 940, 2023, pp. 123–45, doi:https://doi.org/10.1016/j.tcs.2022.10.019.
LibreCat
| DOI
2021 | Book Chapter | LibreCat-ID: 48881
Heins, Jonathan, et al. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, 2021, pp. 1–15.
LibreCat
2020 | Journal Article | LibreCat-ID: 46334
Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing, vol. 88, 2020, p. 105901, doi:https://doi.org/10.1016/j.asoc.2019.105901.
LibreCat
| DOI
2020 | Conference Paper | LibreCat-ID: 48897
Seiler, Moritz, et al. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” Parallel Problem Solving from {Nature} (PPSN XVI), Springer-Verlag, 2020, pp. 48–64, doi:10.1007/978-3-030-58112-1_4.
LibreCat
| DOI
2020 | Journal Article | LibreCat-ID: 48848
Bossek, Jakob, et al. “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.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 48875
Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” Learning and Intelligent Optimization, edited by Roberto Battiti et al., Springer International Publishing, 2019, pp. 215–219, doi:10.1007/978-3-030-05348-2_19.
LibreCat
| DOI
2018 | Conference Paper | LibreCat-ID: 48885
Kerschke, Pascal, et al. “Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2018, pp. 1737–1744, doi:10.1145/3205651.3208233.
LibreCat
| DOI
2018 | Journal Article | LibreCat-ID: 48884
Kerschke, Pascal, et al. “Leveraging TSP Solver Complementarity through Machine Learning.” Evolutionary Computation, vol. 26, no. 4, 2018, pp. 597–620, doi:10.1162/evco_a_00215.
LibreCat
| DOI
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.” Learning and Intelligent Optimization, edited by Paola Festa et al., Springer International Publishing, 2016, pp. 48–59, doi:10.1007/978-3-319-50349-3_4.
LibreCat
| DOI
2012 | Conference Paper | LibreCat-ID: 46396
Bischl, Bernd, et al. “Algorithm Selection Based on Exploratory Landscape Analysis and Cost-Sensitive Learning.” Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, Association for Computing Machinery, 2012, pp. 313–320, doi:10.1145/2330163.2330209.
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| DOI