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90 Publications


2020 | Conference Paper | LibreCat-ID: 48852
Bossek, J., Neumann, A., & Neumann, F. (2020). Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions. Parallel Problem Solving from Nature (PPSN XVI), 346–359. https://doi.org/10.1007/978-3-030-58112-1_24
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2020 | Conference Paper | LibreCat-ID: 48846
Bossek, J., Grimme, C., Rudolph, G., & Trautmann, H. (2020). Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. 2020 IEEE Congress on Evolutionary Computation (CEC), 1–8. https://doi.org/10.1109/CEC48606.2020.9185778
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2020 | Conference Paper | LibreCat-ID: 48879
Do, A. V., Bossek, J., Neumann, A., & Neumann, F. (2020). Evolving Diverse Sets of Tours for the Travelling Salesperson Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 681–689. https://doi.org/10.1145/3377930.3389844
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2020 | Conference Paper | LibreCat-ID: 48895
Roostapour, V., Bossek, J., & Neumann, F. (2020). Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem. Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 551–559. https://doi.org/10.1145/3377930.3390168
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2020 | Conference Paper | LibreCat-ID: 48897
Seiler, M., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. Parallel Problem Solving from {Nature} (PPSN XVI), 48–64. https://doi.org/10.1007/978-3-030-58112-1_4
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2020 | Journal Article | LibreCat-ID: 48848
Bossek, J., Kerschke, P., & Trautmann, H. (2020). A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms. Applied Soft Computing, 88(C). https://doi.org/10.1016/j.asoc.2019.105901
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2020 | Journal Article | LibreCat-ID: 48836
Bartz-Beielstein, T., Doerr, C., van den Berg, D., Bossek, J., Chandrasekaran, S., Eftimov, T., Fischbach, A., Kerschke, P., Cava, W. L., Lopez-Ibanez, M., Malan, K. M., Moore, J. H., Naujoks, B., Orzechowski, P., Volz, V., Wagner, M., & Weise, T. (2020). Benchmarking in Optimization: Best Practice and Open Issues. Corr.
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2020 | Conference Paper | LibreCat-ID: 46330
Seiler, M., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. In T. Bäck, M. Preuss, A. Deutz, H. Wang, C. Doerr, M. Emmerich, & H. Trautmann (Eds.), Proceedings of the 16$^th$ International Conference on Parallel Problem Solving from Nature (PPSN XVI) (pp. 48–64). https://doi.org/10.1007/978-3-030-58112-1_4
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2020 | Journal Article | LibreCat-ID: 46334
Bossek, J., Kerschke, P., & Trautmann, H. (2020). A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Applied Soft Computing, 88, 105901. https://doi.org/10.1016/j.asoc.2019.105901
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2020 | Conference Paper | LibreCat-ID: 46322
Bossek, J., Grimme, C., Rudolph, G., & Trautmann, H. (2020). Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8. https://doi.org/10.1109/CEC48606.2020.9185778
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2020 | Conference Paper | LibreCat-ID: 46324
Bossek, J., Kerschke, P., & Trautmann, H. (2020). Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 1–8.
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2020 | Conference Paper | LibreCat-ID: 46323
Bossek, J., Grimme, C., & Trautmann, H. (2020). Dynamic Bi-Objective Routing of Multiple Vehicles. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’20), 166–174.
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2019 | Conference Paper | LibreCat-ID: 48841
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. A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (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: 48842
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. Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 58–71. https://doi.org/10.1145/3299904.3340307
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2019 | Conference Paper | LibreCat-ID: 48843
Bossek, J., Neumann, F., Peng, P., & Sudholt, D. (2019). Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring. Proceedings of the Genetic and Evolutionary Computation Conference, 1443–1451. https://doi.org/10.1145/3321707.3321792
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2019 | Conference Paper | LibreCat-ID: 48840
Bossek, J., Grimme, C., & Neumann, F. (2019). On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 516–523. https://doi.org/10.1145/3321707.3321818
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2019 | Conference Paper | LibreCat-ID: 48858
Bossek, J., & Grimme, C. (2019). Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems. In R. Battiti, M. Brunato, I. Kotsireas, & P. M. Pardalos (Eds.), Learning and Intelligent Optimization (pp. 184–198). Springer International Publishing. https://doi.org/10.1007/978-3-030-05348-2_17
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2019 | Conference Paper | LibreCat-ID: 48870
Bossek, J., & Sudholt, D. (2019). Time Complexity Analysis of RLS and (1 + 1) EA for the Edge Coloring Problem. Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 102–115. https://doi.org/10.1145/3299904.3340311
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2019 | Conference Paper | LibreCat-ID: 48875
Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, & P. M. Pardalos (Eds.), Learning and Intelligent Optimization (pp. 215–219). Springer International Publishing. https://doi.org/10.1007/978-3-030-05348-2_19
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2019 | Journal Article | LibreCat-ID: 48877
Casalicchio, G., Bossek, J., Lang, M., Kirchhoff, D., Kerschke, P., Hofner, B., Seibold, H., Vanschoren, J., & Bischl, B. (2019). OpenML: An R Package to Connect to the Machine Learning Platform OpenML. Computational Statistics, 34(3), 977–991. https://doi.org/10.1007/s00180-017-0742-2
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