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.”https://doi.org/10.1145/3583131.3590384__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: /record/48869
DOI: 10.1145/3583131.3590384

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.”https://doi.org/10.1016/j.tcs.2022.10.019__Theoretical Computer Science 940 (2023): 123–45.https://doi.org/10.1016/j.tcs.2022.10.019 .
LibreCat: /record/46310
DOI: https://doi.org/10.1016/j.tcs.2022.10.019

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: /record/48881

Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.”https://doi.org/10.1145/3449639.3459384__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: /record/48893
DOI: 10.1145/3449639.3459384

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: /record/48892

Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.”https://doi.org/10.1016/j.asoc.2019.105901__Applied Soft Computing 88 (2020): 105901.https://doi.org/10.1016/j.asoc.2019.105901 .
LibreCat: /record/46334
DOI: https://doi.org/10.1016/j.asoc.2019.105901

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.”https://doi.org/10.1007/978-3-030-58112-1_4__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: /record/48897
DOI: 10.1007/978-3-030-58112-1_4

Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.”https://doi.org/10.1016/j.asoc.2019.105901__Applied Soft Computing 88, no. C (2020).https://doi.org/10.1016/j.asoc.2019.105901 .
LibreCat: /record/48848
DOI: 10.1016/j.asoc.2019.105901

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.”https://doi.org/10.1145/3299904.3340307__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: /record/48842
DOI: 10.1145/3299904.3340307

Nallaperuma, Samadhi, Markus Wagner, Frank Neumann, Bernd Bischl, Olaf Mersmann, and Heike Trautmann. “A Feature-Based Comparison of Local Search and the Christofides Algorithm for the Travelling Salesperson Problem.”https://doi.org/10.1145/2460239.2460253__In Proceedings of the Twelfth Workshop on Foundations of Genetic Algorithms XII, 147–160. FOGA XII ’13. New York, NY, USA: Association for Computing Machinery, 2013.https://doi.org/10.1145/2460239.2460253 .
LibreCat: /record/46388
DOI: 10.1145/2460239.2460253