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90 Publications


2019 | Conference Paper | LibreCat-ID: 46339
Bossek, Jakob, Pascal Kerschke, Aneta Neumann, Markus Wagner, Frank Neumann, and Heike Trautmann. “Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators.” In Proceedings of the 15$^th$ ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV), edited by Tobias Friedrich, Carola Doerr, and Dirk Arnold, 58–71. Potsdam, Germany, 2019. https://doi.org/10.1145/3299904.3340307.
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2019 | Conference Paper | LibreCat-ID: 46338
Bossek, Jakob, Christian Grimme, Stephan Meisel, Günter Rudolph, and Heike Trautmann. “Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm.” In Evolutionary Multi-Criterion Optimization (EMO), edited by Kalyanmoy Deb, Erik Goodman, Coello Carlos A. Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, 11411:516–528. Lecture Notes in Computer Science. East Lansing, Michigan, USA: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-12598-1_41.
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2019 | Conference Paper | LibreCat-ID: 46337
Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” In Learning and Intelligent Optimization, edited by R Battiti, M Brunato, I Kotsireas, and P Pardalos, 11353:215–219. Lecture Notes in Computer Science. Cham: Springer, 2019.
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2018 | Conference Paper | LibreCat-ID: 48839
Bossek, Jakob, Christian Grimme, Stephan Meisel, Günter Rudolph, and Heike Trautmann. “Local Search Effects in Bi-Objective Orienteering.” In Proceedings of the Genetic and Evolutionary Computation Conference, 585–592. GECCO ’18. New York, NY, USA: Association for Computing Machinery, 2018. https://doi.org/10.1145/3205455.3205548.
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2018 | Conference Paper | LibreCat-ID: 48867
Bossek, Jakob. “Performance Assessment of Multi-Objective Evolutionary Algorithms with the R Package Ecr.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1350–1356. GECCO ’18. New York, NY, USA: Association for Computing Machinery, 2018. https://doi.org/10.1145/3205651.3208312.
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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 | Book | LibreCat-ID: 48880
Grimme, Christian, and Jakob Bossek. Einführung in Die Optimierung - Konzepte, Methoden Und Anwendungen. Springer Vieweg, 2018. https://doi.org/10.1007/978-3-658-21151-6.
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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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2018 | Journal Article | LibreCat-ID: 48866
Bossek, Jakob. “Grapherator: A Modular Multi-Step Graph Generator.” Journal of Open Source Software 3, no. 22 (2018): 528. https://doi.org/10.21105/joss.00528.
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2018 | Conference Paper | LibreCat-ID: 46348
Bossek, Jakob, Christian Grimme, Stephan Meisel, Guenter Rudolph, and Heike Trautmann. “Local Search Effects in Bi-Objective Orienteering.” In Proceedings of the Genetic and Evolutionary Computation Conference, 585–592. GECCO ’18. New York, NY, USA: ACM, 2018. https://doi.org/10.1145/3205455.3205548.
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2018 | Journal Article | LibreCat-ID: 46352
Kerschke, Pascal, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, and Heike Trautmann. “Leveraging TSP Solver Complementarity through Machine Learning.” Evolutionary Computation (ECJ) 26, no. 4 (2018): 597–620. https://doi.org/10.1162/evco_a_00215.
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2018 | Conference Paper | LibreCat-ID: 46349
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 (GECCO ’18) Companion, 1737–1744. Kyoto, Japan, 2018. https://doi.org/10.1145/3205651.3208233.
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2017 | Conference Paper | LibreCat-ID: 48863
Bossek, Jakob. “Ecr 2.0: A Modular Framework for Evolutionary Computation in R.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1187–1193. GECCO ’17. New York, NY, USA: Association for Computing Machinery, 2017. https://doi.org/10.1145/3067695.3082470.
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2017 | Conference Paper | LibreCat-ID: 48857
Bossek, Jakob, and Christian Grimme. “A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem.” In 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1–8, 2017. https://doi.org/10.1109/SSCI.2017.8285183.
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2017 | Conference Paper | LibreCat-ID: 48856
Bossek, Jakob, and Christian Grimme. “An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling.” In 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1–8, 2017. https://doi.org/10.1109/SSCI.2017.8285224.
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2017 | Journal Article | LibreCat-ID: 48864
Bossek, Jakob. “McMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem.” Journal of Open Source Software 2, no. 17 (2017): 374. https://doi.org/10.21105/joss.00374.
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2017 | Journal Article | LibreCat-ID: 48865
Bossek, Jakob. “Smoof: Single- and Multi-Objective Optimization Test Functions.” The R Journal 9, no. 1 (2017): 103–113.
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2017 | Journal Article | LibreCat-ID: 48837
Bischl, Bernd, Jakob Richter, Jakob Bossek, Daniel Horn, Janek Thomas, and Michel Lang. “MlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions.” CoRR, 2017.
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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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2016 | Conference Paper | LibreCat-ID: 48874
Bossek, Jakob, and Heike Trautmann. “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, 3–12. AI*IA 2016. Berlin, Heidelberg: Springer-Verlag, 2016. https://doi.org/10.1007/978-3-319-49130-1_1.
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