Jakob Bossek

Fakultät für Elektrotechnik, Informatik und Mathematik
jakob.bossek@uni-paderborn.de
ID
102979

64 Publications

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[64]
2024 | Conference Paper | LibreCat-ID: 52749
Vinzent Seiler, Moritz, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.” In 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2024. https://doi.org/10.1109/ssci52147.2023.10372008.
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[63]
2023 | Conference Paper | LibreCat-ID: 48869
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 248–256. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3583131.3590384.
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[62]
2023 | Conference Paper | LibreCat-ID: 48872
Bossek, Jakob, and Dirk Sudholt. “Runtime Analysis of Quality Diversity Algorithms.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1546–1554. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3583131.3590383.
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[61]
2023 | Conference Paper | LibreCat-ID: 48886
Marrero, Alejandro, Eduardo Segredo, Emma Hart, Jakob Bossek, and Aneta Neumann. “Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space.” In Proceedings of the Genetic} and Evolutionary Computation Conference, 312–320. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3583131.3590504.
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[60]
2023 | Journal Article | LibreCat-ID: 48871
Bossek, Jakob, and Dirk Sudholt. “Do Additional Target Points Speed Up Evolutionary Algorithms?” Theoretical Computer Science, 2023, 113757. https://doi.org/10.1016/j.tcs.2023.113757.
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[59]
2023 | Journal Article | LibreCat-ID: 48859
Bossek, Jakob, and Christian Grimme. “On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem.” Evolutionary Computation, 2023, 1–35. https://doi.org/10.1162/evco_a_00335.
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[58]
2023 | Journal Article | LibreCat-ID: 46310
Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “A Study on the Effects of Normalized TSP Features for Automated Algorithm Selection.” Theoretical Computer Science 940 (2023): 123–45. https://doi.org/10.1016/j.tcs.2022.10.019.
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[57]
2023 | Conference Paper | LibreCat-ID: 48898
Seiler, Moritz Vinzent, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.” In 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 361–68, n.d. https://doi.org/10.1109/SSCI52147.2023.10372008.
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[56]
2022 | Conference Paper | LibreCat-ID: 48861
Bossek, Jakob, and Frank Neumann. “Exploring the Feature Space of TSP Instances Using Quality Diversity.” In Proceedings of the Genetic and Evolutionary Computation Conference, 186–194. GECCO ’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3512290.3528851.
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[55]
2022 | Conference Paper | LibreCat-ID: 48868
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 824–842. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3520304.3533626.
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[54]
2022 | Conference Paper | LibreCat-ID: 48882
Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_14.
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[53]
2022 | Conference Paper | LibreCat-ID: 48894
Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\v sar, 237–249. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_17.
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[52]
2022 | Journal Article | LibreCat-ID: 48878
Clever, Lena, Janina Susanne Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Process-Oriented Stream Classification Pipeline: A Literature Review.” Applied Sciences 12, no. 18 (2022): 9094. https://doi.org/10.3390/app12189094.
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[51]
2022 | Conference Paper | LibreCat-ID: 48896
Rook, Jeroen, Heike Trautmann, Jakob Bossek, and Christian Grimme. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3520304.3528998.
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[50]
2021 | Conference Paper | LibreCat-ID: 48853
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” In Proceedings of the Genetic and Evolutionary Computation Conference, 556–564. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459364.
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[49]
2021 | Conference Paper | LibreCat-ID: 48855
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Exact Counting And~Sampling of Optima for the Knapsack Problem.” In Learning and Intelligent Optimization, 40–54. Berlin, Heidelberg: Springer-Verlag, 2021. https://doi.org/10.1007/978-3-030-92121-7_4.
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[48]
2021 | Conference Paper | LibreCat-ID: 48860
Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 198–206. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459363.
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[47]
2021 | Book Chapter | LibreCat-ID: 48862
Bossek, Jakob, and Dirk Sudholt. “Do Additional Optima Speed up Evolutionary Algorithms?” In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 1–11. New York, NY, USA: Association for Computing Machinery, 2021.
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[46]
2021 | Book Chapter | LibreCat-ID: 48881
Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 1–15. New York, NY, USA: Association for Computing Machinery, 2021.
LibreCat
 
[45]
2021 | Conference Paper | LibreCat-ID: 48876
Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1423–1432. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449726.3463165.
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[44]
2021 | Conference Paper | LibreCat-ID: 48893
Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 600–608. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459384.
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[43]
2021 | Conference Paper | LibreCat-ID: 48891
Neumann, Aneta, Jakob Bossek, and Frank Neumann. “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions.” In Proceedings of the Genetic and Evolutionary Computation Conference, 261–269. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459385.
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[42]
2021 | Book Chapter | LibreCat-ID: 48892
Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation.” In Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms, 1–11. New York, NY, USA: Association for Computing Machinery, 2021.
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[41]
2021 | Journal Article | LibreCat-ID: 48854
Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.” Algorithmica 83, no. 10 (2021): 3148–3179. https://doi.org/10.1007/s00453-021-00838-3.
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[40]
2020 | Conference Paper | LibreCat-ID: 48847
Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1277–1285. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390174.
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[39]
2020 | Conference Paper | LibreCat-ID: 48849
Bossek, Jakob, Carola Doerr, Pascal Kerschke, Aneta Neumann, and Frank Neumann. “Evolving Sampling Strategies for One-Shot Optimization Tasks.” In Parallel Problem Solving from Nature (PPSN XVI), 111–124. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_8.
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[38]
2020 | Conference Paper | LibreCat-ID: 48851
Bossek, Jakob, Katrin Casel, Pascal Kerschke, and Frank Neumann. “The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1286–1294. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390243.
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[37]
2020 | Conference Paper | LibreCat-ID: 48845
Bossek, Jakob, Christian Grimme, and Heike Trautmann. “Dynamic Bi-Objective Routing of Multiple Vehicles.” In Proceedings of the Genetic and Evolutionary Computation Conference, 166–174. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390146.
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[36]
2020 | Conference Paper | LibreCat-ID: 48844
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.” In 2020 IEEE Congress on Evolutionary Computation (CEC), 1–8. Glasgow, United Kingdom: IEEE Press, 2020. https://doi.org/10.1109/CEC48606.2020.9185613.
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[35]
2020 | Conference Paper | LibreCat-ID: 48850
Bossek, Jakob, Carola Doerr, and Pascal Kerschke. “Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB.” In Proceedings of the Genetic and Evolutionary Computation Conference, 778–786. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390155.
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[34]
2020 | Conference Paper | LibreCat-ID: 48852
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions.” In Parallel Problem Solving from Nature (PPSN XVI), 346–359. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_24.
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[33]
2020 | Conference Paper | LibreCat-ID: 48846
Bossek, Jakob, Christian Grimme, Günter Rudolph, and Heike Trautmann. “Towards Decision Support in Dynamic Bi-Objective Vehicle Routing.” In 2020 IEEE Congress on Evolutionary Computation (CEC), 1–8. Glasgow, United Kingdom: IEEE Press, 2020. https://doi.org/10.1109/CEC48606.2020.9185778.
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[32]
2020 | Conference Paper | LibreCat-ID: 48879
Do, Anh Viet, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 681–689. GECCO’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3389844.
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[31]
2020 | Conference Paper | LibreCat-ID: 48895
Roostapour, Vahid, Jakob Bossek, and Frank Neumann. “Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem.” In Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 551–559. {GECCO} ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390168.
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[30]
2020 | Conference Paper | LibreCat-ID: 48897
Seiler, Moritz, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” In Parallel Problem Solving from {Nature} (PPSN XVI), 48–64. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_4.
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[29]
2020 | Journal Article | LibreCat-ID: 48848
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing 88, no. C (2020). https://doi.org/10.1016/j.asoc.2019.105901.
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[28]
2020 | Journal Article | LibreCat-ID: 48836
Bartz-Beielstein, Thomas, Carola Doerr, Daan van den Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, et al. “Benchmarking in Optimization: Best Practice and Open Issues.” Corr, 2020.
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[27]
2019 | Conference Paper | LibreCat-ID: 48841
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, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, 516–528. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-12598-1_41.
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[26]
2019 | Conference Paper | LibreCat-ID: 48842
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 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 58–71. FOGA ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3299904.3340307.
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[25]
2019 | Conference Paper | LibreCat-ID: 48843
Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1443–1451. GECCO ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3321707.3321792.
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[24]
2019 | Conference Paper | LibreCat-ID: 48840
Bossek, Jakob, Christian Grimme, and Frank Neumann. “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 516–523. GECCO ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3321707.3321818.
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[23]
2019 | Conference Paper | LibreCat-ID: 48858
Bossek, Jakob, and Christian Grimme. “Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-Criteria Shortest Path Problems.” In Learning and Intelligent Optimization, edited by Roberto Battiti, Mauro Brunato, Ilias Kotsireas, and Panos M. Pardalos, 184–198. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-05348-2_17.
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[22]
2019 | Conference Paper | LibreCat-ID: 48870
Bossek, Jakob, and Dirk Sudholt. “Time Complexity Analysis of RLS and (1 + 1) EA for the Edge Coloring Problem.” In Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 102–115. FOGA ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3299904.3340311.
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[21]
2019 | Conference Paper | LibreCat-ID: 48875
Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” In Learning and Intelligent Optimization, edited by Roberto Battiti, Mauro Brunato, Ilias Kotsireas, and Panos M. Pardalos, 215–219. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-05348-2_19.
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[20]
2019 | Journal Article | LibreCat-ID: 48877
Casalicchio, Giuseppe, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, and Bernd Bischl. “OpenML: An R Package to Connect to the Machine Learning Platform OpenML.” Computational Statistics 34, no. 3 (2019): 977–991. https://doi.org/10.1007/s00180-017-0742-2.
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[19]
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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[18]
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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[17]
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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[16]
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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[15]
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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[14]
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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[13]
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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[12]
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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[11]
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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[10]
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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[9]
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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[8]
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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[7]
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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[6]
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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[5]
2015 | Conference Paper | LibreCat-ID: 48838
Bossek, Jakob, Bernd Bischl, Tobias Wagner, and Günter Rudolph. “Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1319–1326. GECCO ’15. New York, NY, USA: Association for Computing Machinery, 2015. https://doi.org/10.1145/2739480.2754673.
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[4]
2015 | Conference Paper | LibreCat-ID: 48887
Meisel, Stephan, Christian Grimme, Jakob Bossek, Martin Wölck, Günter Rudolph, and Heike Trautmann. “Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle.” In Proceedings of the Genetic and Evolutionary Computation Conference , 425–432. GECCO’15. New York, NY, USA: Association for Computing Machinery, 2015. https://doi.org/10.1145/2739480.2754705.
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[3]
2013 | Journal Article | LibreCat-ID: 48889
Mersmann, Olaf, Bernd Bischl, Heike Trautmann, Markus Wagner, Jakob Bossek, and Frank Neumann. “A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem.” Annals of Mathematics and Artificial Intelligence 69, no. 2 (2013): 151–182. https://doi.org/10.1007/s10472-013-9341-2.
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[2]
2012 | Conference Paper | LibreCat-ID: 48890
Mersmann, Olaf, Bernd Bischl, Jakob Bossek, Heike Trautmann, Markus Wagner, and Frank Neumann. “Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness.” In Revised Selected Papers of the 6th International Conference on Learning and Intelligent Optimization - Volume 7219, 115–129. LION 6. Berlin, Heidelberg: Springer-Verlag, 2012.
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[1]
2012 | Book Chapter | LibreCat-ID: 48888
Mersmann, Olaf, Bernd Bischl, Jakob Bossek, Heike Trautmann, Markus Wagner, and Frank Neumann. “Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness.” In Learning and Intelligent Optimization, 7219:115–129. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. https://doi.org/10.1007/978-3-642-34413-8_9.
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64 Publications

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[64]
2024 | Conference Paper | LibreCat-ID: 52749
Vinzent Seiler, Moritz, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.” In 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2024. https://doi.org/10.1109/ssci52147.2023.10372008.
LibreCat | DOI
 
[63]
2023 | Conference Paper | LibreCat-ID: 48869
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 248–256. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3583131.3590384.
LibreCat | DOI
 
[62]
2023 | Conference Paper | LibreCat-ID: 48872
Bossek, Jakob, and Dirk Sudholt. “Runtime Analysis of Quality Diversity Algorithms.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1546–1554. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3583131.3590383.
LibreCat | DOI
 
[61]
2023 | Conference Paper | LibreCat-ID: 48886
Marrero, Alejandro, Eduardo Segredo, Emma Hart, Jakob Bossek, and Aneta Neumann. “Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space.” In Proceedings of the Genetic} and Evolutionary Computation Conference, 312–320. GECCO’23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3583131.3590504.
LibreCat | DOI
 
[60]
2023 | Journal Article | LibreCat-ID: 48871
Bossek, Jakob, and Dirk Sudholt. “Do Additional Target Points Speed Up Evolutionary Algorithms?” Theoretical Computer Science, 2023, 113757. https://doi.org/10.1016/j.tcs.2023.113757.
LibreCat | DOI
 
[59]
2023 | Journal Article | LibreCat-ID: 48859
Bossek, Jakob, and Christian Grimme. “On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem.” Evolutionary Computation, 2023, 1–35. https://doi.org/10.1162/evco_a_00335.
LibreCat | DOI
 
[58]
2023 | Journal Article | LibreCat-ID: 46310
Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “A Study on the Effects of Normalized TSP Features for Automated Algorithm Selection.” Theoretical Computer Science 940 (2023): 123–45. https://doi.org/10.1016/j.tcs.2022.10.019.
LibreCat | DOI
 
[57]
2023 | Conference Paper | LibreCat-ID: 48898
Seiler, Moritz Vinzent, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.” In 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 361–68, n.d. https://doi.org/10.1109/SSCI52147.2023.10372008.
LibreCat | DOI
 
[56]
2022 | Conference Paper | LibreCat-ID: 48861
Bossek, Jakob, and Frank Neumann. “Exploring the Feature Space of TSP Instances Using Quality Diversity.” In Proceedings of the Genetic and Evolutionary Computation Conference, 186–194. GECCO ’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3512290.3528851.
LibreCat | DOI
 
[55]
2022 | Conference Paper | LibreCat-ID: 48868
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 824–842. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3520304.3533626.
LibreCat | DOI
 
[54]
2022 | Conference Paper | LibreCat-ID: 48882
Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_14.
LibreCat | DOI
 
[53]
2022 | Conference Paper | LibreCat-ID: 48894
Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\v sar, 237–249. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_17.
LibreCat | DOI
 
[52]
2022 | Journal Article | LibreCat-ID: 48878
Clever, Lena, Janina Susanne Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Process-Oriented Stream Classification Pipeline: A Literature Review.” Applied Sciences 12, no. 18 (2022): 9094. https://doi.org/10.3390/app12189094.
LibreCat | DOI
 
[51]
2022 | Conference Paper | LibreCat-ID: 48896
Rook, Jeroen, Heike Trautmann, Jakob Bossek, and Christian Grimme. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3520304.3528998.
LibreCat | DOI
 
[50]
2021 | Conference Paper | LibreCat-ID: 48853
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” In Proceedings of the Genetic and Evolutionary Computation Conference, 556–564. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459364.
LibreCat | DOI
 
[49]
2021 | Conference Paper | LibreCat-ID: 48855
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Exact Counting And~Sampling of Optima for the Knapsack Problem.” In Learning and Intelligent Optimization, 40–54. Berlin, Heidelberg: Springer-Verlag, 2021. https://doi.org/10.1007/978-3-030-92121-7_4.
LibreCat | DOI
 
[48]
2021 | Conference Paper | LibreCat-ID: 48860
Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 198–206. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459363.
LibreCat | DOI
 
[47]
2021 | Book Chapter | LibreCat-ID: 48862
Bossek, Jakob, and Dirk Sudholt. “Do Additional Optima Speed up Evolutionary Algorithms?” In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 1–11. New York, NY, USA: Association for Computing Machinery, 2021.
LibreCat
 
[46]
2021 | Book Chapter | LibreCat-ID: 48881
Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “On the Potential of Normalized TSP Features for Automated Algorithm Selection.” In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 1–15. New York, NY, USA: Association for Computing Machinery, 2021.
LibreCat
 
[45]
2021 | Conference Paper | LibreCat-ID: 48876
Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1423–1432. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449726.3463165.
LibreCat | DOI
 
[44]
2021 | Conference Paper | LibreCat-ID: 48893
Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 600–608. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459384.
LibreCat | DOI
 
[43]
2021 | Conference Paper | LibreCat-ID: 48891
Neumann, Aneta, Jakob Bossek, and Frank Neumann. “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions.” In Proceedings of the Genetic and Evolutionary Computation Conference, 261–269. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459385.
LibreCat | DOI
 
[42]
2021 | Book Chapter | LibreCat-ID: 48892
Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation.” In Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms, 1–11. New York, NY, USA: Association for Computing Machinery, 2021.
LibreCat
 
[41]
2021 | Journal Article | LibreCat-ID: 48854
Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.” Algorithmica 83, no. 10 (2021): 3148–3179. https://doi.org/10.1007/s00453-021-00838-3.
LibreCat | DOI
 
[40]
2020 | Conference Paper | LibreCat-ID: 48847
Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1277–1285. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390174.
LibreCat | DOI
 
[39]
2020 | Conference Paper | LibreCat-ID: 48849
Bossek, Jakob, Carola Doerr, Pascal Kerschke, Aneta Neumann, and Frank Neumann. “Evolving Sampling Strategies for One-Shot Optimization Tasks.” In Parallel Problem Solving from Nature (PPSN XVI), 111–124. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_8.
LibreCat | DOI
 
[38]
2020 | Conference Paper | LibreCat-ID: 48851
Bossek, Jakob, Katrin Casel, Pascal Kerschke, and Frank Neumann. “The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1286–1294. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390243.
LibreCat | DOI
 
[37]
2020 | Conference Paper | LibreCat-ID: 48845
Bossek, Jakob, Christian Grimme, and Heike Trautmann. “Dynamic Bi-Objective Routing of Multiple Vehicles.” In Proceedings of the Genetic and Evolutionary Computation Conference, 166–174. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390146.
LibreCat | DOI
 
[36]
2020 | Conference Paper | LibreCat-ID: 48844
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.” In 2020 IEEE Congress on Evolutionary Computation (CEC), 1–8. Glasgow, United Kingdom: IEEE Press, 2020. https://doi.org/10.1109/CEC48606.2020.9185613.
LibreCat | DOI
 
[35]
2020 | Conference Paper | LibreCat-ID: 48850
Bossek, Jakob, Carola Doerr, and Pascal Kerschke. “Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB.” In Proceedings of the Genetic and Evolutionary Computation Conference, 778–786. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390155.
LibreCat | DOI
 
[34]
2020 | Conference Paper | LibreCat-ID: 48852
Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions.” In Parallel Problem Solving from Nature (PPSN XVI), 346–359. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_24.
LibreCat | DOI
 
[33]
2020 | Conference Paper | LibreCat-ID: 48846
Bossek, Jakob, Christian Grimme, Günter Rudolph, and Heike Trautmann. “Towards Decision Support in Dynamic Bi-Objective Vehicle Routing.” In 2020 IEEE Congress on Evolutionary Computation (CEC), 1–8. Glasgow, United Kingdom: IEEE Press, 2020. https://doi.org/10.1109/CEC48606.2020.9185778.
LibreCat | DOI
 
[32]
2020 | Conference Paper | LibreCat-ID: 48879
Do, Anh Viet, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 681–689. GECCO’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3389844.
LibreCat | DOI
 
[31]
2020 | Conference Paper | LibreCat-ID: 48895
Roostapour, Vahid, Jakob Bossek, and Frank Neumann. “Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem.” In Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 551–559. {GECCO} ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390168.
LibreCat | DOI
 
[30]
2020 | Conference Paper | LibreCat-ID: 48897
Seiler, Moritz, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” In Parallel Problem Solving from {Nature} (PPSN XVI), 48–64. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_4.
LibreCat | DOI
 
[29]
2020 | Journal Article | LibreCat-ID: 48848
Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” Applied Soft Computing 88, no. C (2020). https://doi.org/10.1016/j.asoc.2019.105901.
LibreCat | DOI
 
[28]
2020 | Journal Article | LibreCat-ID: 48836
Bartz-Beielstein, Thomas, Carola Doerr, Daan van den Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, et al. “Benchmarking in Optimization: Best Practice and Open Issues.” Corr, 2020.
LibreCat
 
[27]
2019 | Conference Paper | LibreCat-ID: 48841
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, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, 516–528. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-12598-1_41.
LibreCat | DOI
 
[26]
2019 | Conference Paper | LibreCat-ID: 48842
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 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 58–71. FOGA ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3299904.3340307.
LibreCat | DOI
 
[25]
2019 | Conference Paper | LibreCat-ID: 48843
Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1443–1451. GECCO ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3321707.3321792.
LibreCat | DOI
 
[24]
2019 | Conference Paper | LibreCat-ID: 48840
Bossek, Jakob, Christian Grimme, and Frank Neumann. “On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem.” In Proceedings of the Genetic and Evolutionary Computation Conference, 516–523. GECCO ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3321707.3321818.
LibreCat | DOI
 
[23]
2019 | Conference Paper | LibreCat-ID: 48858
Bossek, Jakob, and Christian Grimme. “Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-Criteria Shortest Path Problems.” In Learning and Intelligent Optimization, edited by Roberto Battiti, Mauro Brunato, Ilias Kotsireas, and Panos M. Pardalos, 184–198. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-05348-2_17.
LibreCat | DOI
 
[22]
2019 | Conference Paper | LibreCat-ID: 48870
Bossek, Jakob, and Dirk Sudholt. “Time Complexity Analysis of RLS and (1 + 1) EA for the Edge Coloring Problem.” In Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 102–115. FOGA ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3299904.3340311.
LibreCat | DOI
 
[21]
2019 | Conference Paper | LibreCat-ID: 48875
Bossek, Jakob, and Heike Trautmann. “Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.” In Learning and Intelligent Optimization, edited by Roberto Battiti, Mauro Brunato, Ilias Kotsireas, and Panos M. Pardalos, 215–219. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-05348-2_19.
LibreCat | DOI
 
[20]
2019 | Journal Article | LibreCat-ID: 48877
Casalicchio, Giuseppe, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, and Bernd Bischl. “OpenML: An R Package to Connect to the Machine Learning Platform OpenML.” Computational Statistics 34, no. 3 (2019): 977–991. https://doi.org/10.1007/s00180-017-0742-2.
LibreCat | DOI
 
[19]
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.
LibreCat | DOI
 
[18]
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.
LibreCat | DOI
 
[17]
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.
LibreCat | DOI
 
[16]
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.
LibreCat | DOI
 
[15]
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.
LibreCat | DOI
 
[14]
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.
LibreCat | DOI
 
[13]
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.
LibreCat | DOI
 
[12]
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.
LibreCat | DOI
 
[11]
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.
LibreCat | DOI
 
[10]
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.
LibreCat | DOI
 
[9]
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.
LibreCat
 
[8]
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.
LibreCat
 
[7]
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.
LibreCat | DOI
 
[6]
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.
LibreCat | DOI
 
[5]
2015 | Conference Paper | LibreCat-ID: 48838
Bossek, Jakob, Bernd Bischl, Tobias Wagner, and Günter Rudolph. “Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1319–1326. GECCO ’15. New York, NY, USA: Association for Computing Machinery, 2015. https://doi.org/10.1145/2739480.2754673.
LibreCat | DOI
 
[4]
2015 | Conference Paper | LibreCat-ID: 48887
Meisel, Stephan, Christian Grimme, Jakob Bossek, Martin Wölck, Günter Rudolph, and Heike Trautmann. “Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle.” In Proceedings of the Genetic and Evolutionary Computation Conference , 425–432. GECCO’15. New York, NY, USA: Association for Computing Machinery, 2015. https://doi.org/10.1145/2739480.2754705.
LibreCat | DOI
 
[3]
2013 | Journal Article | LibreCat-ID: 48889
Mersmann, Olaf, Bernd Bischl, Heike Trautmann, Markus Wagner, Jakob Bossek, and Frank Neumann. “A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem.” Annals of Mathematics and Artificial Intelligence 69, no. 2 (2013): 151–182. https://doi.org/10.1007/s10472-013-9341-2.
LibreCat | DOI
 
[2]
2012 | Conference Paper | LibreCat-ID: 48890
Mersmann, Olaf, Bernd Bischl, Jakob Bossek, Heike Trautmann, Markus Wagner, and Frank Neumann. “Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness.” In Revised Selected Papers of the 6th International Conference on Learning and Intelligent Optimization - Volume 7219, 115–129. LION 6. Berlin, Heidelberg: Springer-Verlag, 2012.
LibreCat
 
[1]
2012 | Book Chapter | LibreCat-ID: 48888
Mersmann, Olaf, Bernd Bischl, Jakob Bossek, Heike Trautmann, Markus Wagner, and Frank Neumann. “Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness.” In Learning and Intelligent Optimization, 7219:115–129. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. https://doi.org/10.1007/978-3-642-34413-8_9.
LibreCat | DOI
 
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