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19 Publications
    2023 |  Conference Paper | LibreCat-ID: 48869 
    
      Bossek, Jakob, et al. “On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2023, pp. 248–256, doi:10.1145/3583131.3590384.
    
    
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    2023 |  Journal Article | LibreCat-ID: 48871 
    
      Bossek, Jakob, and Dirk Sudholt. “Do Additional Target Points Speed Up Evolutionary Algorithms?” Theoretical Computer Science, 2023, p. 113757, doi:10.1016/j.tcs.2023.113757.
    
    
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    2022 |  Conference Paper | LibreCat-ID: 48894 
    
      Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249, doi:10.1007/978-3-031-14714-2_17.
    
    
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    2021 |  Conference Paper | LibreCat-ID: 48853 
    
      Bossek, Jakob, et al. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2021, pp. 556–564, doi:10.1145/3449639.3459364.
    
    
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    2021 |  Conference Paper | LibreCat-ID: 48860 
    
      Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2021, pp. 198–206, doi:10.1145/3449639.3459363.
    
    
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    2021 |  Book Chapter | LibreCat-ID: 48862 
    
      Bossek, Jakob, and Dirk Sudholt. “Do Additional Optima Speed up Evolutionary Algorithms?” Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, 2021, pp. 1–11.
    
    
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    2021 |  Conference Paper | LibreCat-ID: 48876 
    
      Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences for More than Just Two Algorithms.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2021, pp. 1423–1432, doi:10.1145/3449726.3463165.
    
    
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    2021 |  Conference Paper | LibreCat-ID: 48893 
    
      Nikfarjam, Adel, et al. “Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2021, pp. 600–608, doi:10.1145/3449639.3459384.
    
    
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    2021 |  Conference Paper | LibreCat-ID: 48891 
    
      Neumann, Aneta, et al. “Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2021, pp. 261–269, doi:10.1145/3449639.3459385.
    
    
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    2021 |  Book Chapter | LibreCat-ID: 48892 
    
      Nikfarjam, Adel, et al. “Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation.” Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, 2021, pp. 1–11.
    
    
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    2021 |  Journal Article | LibreCat-ID: 48854 
    
      Bossek, Jakob, et al. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.” Algorithmica, vol. 83, no. 10, 2021, pp. 3148–3179, doi:10.1007/s00453-021-00838-3.
    
    
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    2020 |  Conference Paper | LibreCat-ID: 48847 
    
      Bossek, Jakob, et al. “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2020, pp. 1277–1285, doi:10.1145/3377930.3390174.
    
    
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    2020 |  Conference Paper | LibreCat-ID: 48851 
    
      Bossek, Jakob, et al. “The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2020, pp. 1286–1294, doi:10.1145/3377930.3390243.
    
    
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    2020 |  Conference Paper | LibreCat-ID: 48845 
    
      Bossek, Jakob, et al. “Dynamic Bi-Objective Routing of Multiple Vehicles.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2020, pp. 166–174, doi:10.1145/3377930.3390146.
    
    
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    2020 |  Conference Paper | LibreCat-ID: 48852 
    
      Bossek, Jakob, et al. “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), Springer-Verlag, 2020, pp. 346–359, doi:10.1007/978-3-030-58112-1_24.
    
    
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    2020 |  Conference Paper | LibreCat-ID: 48879 
    
      Do, Anh Viet, et al. “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2020, pp. 681–689, doi:10.1145/3377930.3389844.
    
    
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    2020 |  Conference Paper | LibreCat-ID: 48895 
    
      Roostapour, Vahid, et al. “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, Association for Computing Machinery, 2020, pp. 551–559, doi:10.1145/3377930.3390168.
    
    
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    2019 |  Conference Paper | LibreCat-ID: 48843 
    
      Bossek, Jakob, et al. “Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2019, pp. 1443–1451, doi:10.1145/3321707.3321792.
    
    
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    2015 |  Conference Paper | LibreCat-ID: 48838 
    
      Bossek, Jakob, et al. “Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2015, pp. 1319–1326, doi:10.1145/2739480.2754673.
    
    
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