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90 Publications


2019 | Conference Paper | LibreCat-ID: 46339
Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., & Trautmann, H. (2019). Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators. In T. Friedrich, C. Doerr, & D. Arnold (Eds.), Proceedings of the 15$^th$ ACM/SIGEVO Workshop on Foundations of Genetic Algorithms (FOGA XV) (pp. 58–71). https://doi.org/10.1145/3299904.3340307
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2019 | Conference Paper | LibreCat-ID: 46338
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2019). Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary Algorithm. In K. Deb, E. Goodman, C. C. A. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (Vol. 11411, pp. 516–528). Springer International Publishing. https://doi.org/10.1007/978-3-030-12598-1_41
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2019 | Conference Paper | LibreCat-ID: 46337
Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, & P. Pardalos (Eds.), Learning and Intelligent Optimization (Vol. 11353, pp. 215–219). Springer.
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2018 | Conference Paper | LibreCat-ID: 48839
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2018). Local Search Effects in Bi-Objective Orienteering. Proceedings of the Genetic and Evolutionary Computation Conference, 585–592. https://doi.org/10.1145/3205455.3205548
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2018 | Conference Paper | LibreCat-ID: 48867
Bossek, J. (2018). Performance Assessment of Multi-Objective Evolutionary Algorithms with the R Package ecr. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1350–1356. https://doi.org/10.1145/3205651.3208312
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2018 | Conference Paper | LibreCat-ID: 48885
Kerschke, P., Bossek, J., & Trautmann, H. (2018). 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, 1737–1744. https://doi.org/10.1145/3205651.3208233
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2018 | Book | LibreCat-ID: 48880
Grimme, C., & Bossek, J. (2018). Einführung in die Optimierung - Konzepte, Methoden und Anwendungen. Springer Vieweg. https://doi.org/10.1007/978-3-658-21151-6
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2018 | Journal Article | LibreCat-ID: 48884
Kerschke, P., Kotthoff, L., Bossek, J., Hoos, H. H., & Trautmann, H. (2018). Leveraging TSP Solver Complementarity through Machine Learning. Evolutionary Computation, 26(4), 597–620. https://doi.org/10.1162/evco_a_00215
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2018 | Journal Article | LibreCat-ID: 48866
Bossek, J. (2018). Grapherator: A Modular Multi-Step Graph Generator. Journal of Open Source Software, 3(22), 528. https://doi.org/10.21105/joss.00528
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2018 | Conference Paper | LibreCat-ID: 46348
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2018). Local Search Effects in Bi-Objective Orienteering. Proceedings of the Genetic and Evolutionary Computation Conference, 585–592. https://doi.org/10.1145/3205455.3205548
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2018 | Journal Article | LibreCat-ID: 46352
Kerschke, P., Kotthoff, L., Bossek, J., Hoos, H. H., & Trautmann, H. (2018). Leveraging TSP Solver Complementarity through Machine Learning. Evolutionary Computation (ECJ), 26(4), 597–620. https://doi.org/10.1162/evco_a_00215
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2018 | Conference Paper | LibreCat-ID: 46349
Kerschke, P., Bossek, J., & Trautmann, H. (2018). Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’18) Companion, 1737–1744. https://doi.org/10.1145/3205651.3208233
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2017 | Conference Paper | LibreCat-ID: 48863
Bossek, J. (2017). Ecr 2.0: A Modular Framework for Evolutionary Computation in R. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1187–1193. https://doi.org/10.1145/3067695.3082470
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2017 | Conference Paper | LibreCat-ID: 48857
Bossek, J., & Grimme, C. (2017). A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem. 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1–8. https://doi.org/10.1109/SSCI.2017.8285183
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2017 | Conference Paper | LibreCat-ID: 48856
Bossek, J., & Grimme, C. (2017). An Extended Mutation-Based Priority-Rule Integration Concept for Multi-Objective Machine Scheduling. 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1–8. https://doi.org/10.1109/SSCI.2017.8285224
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2017 | Journal Article | LibreCat-ID: 48864
Bossek, J. (2017). mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem. Journal of Open Source Software, 2(17), 374. https://doi.org/10.21105/joss.00374
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2017 | Journal Article | LibreCat-ID: 48865
Bossek, J. (2017). Smoof: Single- and Multi-Objective Optimization Test Functions. The R Journal, 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. (2017). mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions. CoRR.
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2016 | Conference Paper | LibreCat-ID: 48873
Bossek, J., & Trautmann, H. (2016). Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization (pp. 48–59). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_4
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2016 | Conference Paper | LibreCat-ID: 48874
Bossek, J., & Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037, 3–12. https://doi.org/10.1007/978-3-319-49130-1_1
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