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 .

Bossek, Jakob, and Dirk Sudholt. “Do Additional Target Points Speed Up Evolutionary Algorithms?”https://doi.org/10.1016/j.tcs.2023.113757__Theoretical Computer Science, 2023, 113757.https://doi.org/10.1016/j.tcs.2023.113757 .

Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.”https://doi.org/10.1007/978-3-031-14714-2_17__In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\'76 sar, 237–249. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022.https://doi.org/10.1007/978-3-031-14714-2_17 .

Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.”https://doi.org/10.1145/3449639.3459364__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 .

Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.”https://doi.org/10.1145/3449639.3459363__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 .

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.

Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.”https://doi.org/10.1145/3449726.3463165__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 .

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 .

Neumann, Aneta, Jakob Bossek, and Frank Neumann. “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions.”https://doi.org/10.1145/3449639.3459385__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 .

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.

Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.”https://doi.org/10.1007/s00453-021-00838-3__Algorithmica 83, no. 10 (2021): 3148–3179.https://doi.org/10.1007/s00453-021-00838-3 .

Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.”https://doi.org/10.1145/3377930.3390174__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 .

Bossek, Jakob, Katrin Casel, Pascal Kerschke, and Frank Neumann. “The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics.”https://doi.org/10.1145/3377930.3390243__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 .

Bossek, Jakob, Christian Grimme, and Heike Trautmann. “Dynamic Bi-Objective Routing of Multiple Vehicles.”https://doi.org/10.1145/3377930.3390146__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 .

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.”https://doi.org/10.1007/978-3-030-58112-1_24__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 .

Do, Anh Viet, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem.”https://doi.org/10.1145/3377930.3389844__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 .

Roostapour, Vahid, Jakob Bossek, and Frank Neumann. “Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem.”https://doi.org/10.1145/3377930.3390168__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 .

Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring.”https://doi.org/10.1145/3321707.3321792__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 .

Bossek, Jakob, Bernd Bischl, Tobias Wagner, and Günter Rudolph. “Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement.”https://doi.org/10.1145/2739480.2754673__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 .