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 .
LibreCat: /record/48847
DOI: 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 .
LibreCat: /record/48851
DOI: 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 .
LibreCat: /record/48845
DOI: 10.1145/3377930.3390146

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.”https://doi.org/10.1145/3377930.3390155__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: /record/48850
DOI: 10.1145/3377930.3390155

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 .
LibreCat: /record/48879
DOI: 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 .
LibreCat: /record/48895
DOI: 10.1145/3377930.3390168