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85 Publications


2018 | Conference Paper | LibreCat-ID: 48885
Kerschke P, Bossek J, Trautmann H. 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. GECCO’18. Association for Computing Machinery; 2018:1737–1744. doi:10.1145/3205651.3208233
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2018 | Book | LibreCat-ID: 48880
Grimme C, Bossek J. Einführung in Die Optimierung - Konzepte, Methoden Und Anwendungen. Springer Vieweg; 2018. doi:10.1007/978-3-658-21151-6
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2018 | Journal Article | LibreCat-ID: 48884
Kerschke P, Kotthoff L, Bossek J, Hoos HH, Trautmann H. Leveraging TSP Solver Complementarity through Machine Learning. Evolutionary Computation. 2018;26(4):597–620. doi:10.1162/evco_a_00215
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2018 | Journal Article | LibreCat-ID: 48866
Bossek J. Grapherator: A Modular Multi-Step Graph Generator. Journal of Open Source Software. 2018;3(22):528. doi:10.21105/joss.00528
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2018 | Conference Paper | LibreCat-ID: 46348
Bossek J, Grimme C, Meisel S, Rudolph G, Trautmann H. Local Search Effects in Bi-Objective Orienteering. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’18. ACM; 2018:585–592. doi:10.1145/3205455.3205548
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2018 | Journal Article | LibreCat-ID: 46352
Kerschke P, Kotthoff L, Bossek J, Hoos HH, Trautmann H. Leveraging TSP Solver Complementarity through Machine Learning. Evolutionary Computation (ECJ). 2018;26(4):597–620. doi:10.1162/evco_a_00215
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2018 | Conference Paper | LibreCat-ID: 46349
Kerschke P, Bossek J, Trautmann H. 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 (GECCO ’18) Companion. ; 2018:1737–1744. doi:10.1145/3205651.3208233
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2017 | Conference Paper | LibreCat-ID: 48863
Bossek J. Ecr 2.0: A Modular Framework for Evolutionary Computation in R. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO ’17. Association for Computing Machinery; 2017:1187–1193. doi:10.1145/3067695.3082470
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2017 | Conference Paper | LibreCat-ID: 48857
Bossek J, Grimme C. A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI). ; 2017:1–8. doi:10.1109/SSCI.2017.8285183
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2017 | Conference Paper | LibreCat-ID: 48856
Bossek J, Grimme C. An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI). ; 2017:1–8. doi:10.1109/SSCI.2017.8285224
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2017 | Journal Article | LibreCat-ID: 48864
Bossek J. mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem. Journal of Open Source Software. 2017;2(17):374. doi:10.21105/joss.00374
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2017 | Journal Article | LibreCat-ID: 48865
Bossek J. Smoof: Single- and Multi-Objective Optimization Test Functions. The R Journal. 2017;9(1):103–113.
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2017 | Journal Article | LibreCat-ID: 48837
Bischl B, Richter J, Bossek J, Horn D, Thomas J, Lang M. mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions. CoRR. Published online 2017.
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2016 | Conference Paper | LibreCat-ID: 48873
Bossek J, Trautmann H. Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers. In: Festa P, Sellmann M, Vanschoren J, eds. Learning and Intelligent Optimization. Lecture Notes in Computer Science. Springer International Publishing; 2016:48–59. doi:10.1007/978-3-319-50349-3_4
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2016 | Conference Paper | LibreCat-ID: 48874
Bossek J, Trautmann H. Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. In: Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037. AI*IA 2016. Springer-Verlag; 2016:3–12. doi:10.1007/978-3-319-49130-1_1
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2016 | Conference Paper | LibreCat-ID: 46365
Bossek J, Trautmann H. Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers. In: Festa P, Sellmann M, Vanschoren J, eds. Learning and Intelligent Optimization. Vol 10079. Lecture Notes in Computer Science. Springer International Publishing; 2016:48–59. doi:10.1007/978-3-319-50349-3_4
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2016 | Conference Paper | LibreCat-ID: 46366
Bossek J, Trautmann H. Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. In: Adorni G, Cagnoni S, Gori M, Maratea M, eds. AI*IA 2016 Advances in Artificial Intelligence. Vol 10037. Lecture Notes in Computer Science. Springer; 2016:3–12. doi:10.1007/978-3-319-49130-1_1
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2015 | Conference Paper | LibreCat-ID: 48838
Bossek J, Bischl B, Wagner T, Rudolph G. Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’15. Association for Computing Machinery; 2015:1319–1326. doi:10.1145/2739480.2754673
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2015 | Conference Paper | LibreCat-ID: 48887
Meisel S, Grimme C, Bossek J, Wölck M, Rudolph G, Trautmann H. Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. In: Proceedings of the Genetic and Evolutionary Computation Conference . GECCO’15. Association for Computing Machinery; 2015:425–432. doi:10.1145/2739480.2754705
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2015 | Conference Paper | LibreCat-ID: 46377
Meisel S, Grimme C, Bossek J, Wölck M, Rudolph G, Trautmann H. Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’15). ; 2015:425–432. doi:10.1145/2739480.2754705
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