2021-2023 Publications

• 2023
  • C. Doerr, M. Krejca : “Run Time Analysis for Random Local Search on Generalized Majority Functions”, IEEE Transactions on Evolutionary Computation, vol. 27 (5), pp. 1385-1397, (Institute of Electrical and Electronics Engineers) (2023)
• 2022
  • S. Cohen, Ph. Fischbeck, T. Friedrich, M. Krejca, Th. Sauerwald : “Accelerated Information Dissemination on Networks with Local and Global Edges”, 29^th International Colloquium on Structural Information and Communication Complexity (SIROCCO), Paderborn, Germany, pp. 79-97 (2022)
  • T. Friedrich, A. Göbel, M. Katzmann, M. Krejca, M. Pappik : “Algorithms for hard-constraint point processes via discretization”, International Computing and Combinatorics Conference (COCOON), Shenzhen, China, pp. 242-254, (Springer) (2022)
  • T. Friedrich, T. Kötzing, M. Krejca, A. Rajabi : “Escaping Local Optima With Local Search: A Theory-Driven Discussion”, Parallel Problem Solving from Nature (PPSN) XVII, Dortmund, Germany, pp. 442-455 (2022)
  • A. Biedenkapp, N. Dang, M. Krejca, F. Hutter, C. Doerr : “Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration”, GECCO '22: Genetic and Evolutionary Computation Conference, Boston, United States, pp. 766-775 (2022)
• 2021
  • Th. Bläsius, T. Friedrich, M. Krejca, L. Molitor : “The Impact of Geometry on Monochrome Regions in the Flip Schelling Process”, The 32^nd International Symposium on Algorithms and Computation (ISAAC 2021), Fukuoka, Japan, pp. 29:1-29:17 (2021)
  • T. Friedrich, A. Göbel, M. Krejca, M. Pappik : “A spectral independence view on hard spheres via block dynamics”, Proceedings of the International Colloquium on Automata, Languages and Programming 2021, vol. 198, Glasgow, United Kingdom, pp. 66:1-66:15 (2021)
  • M. Böther, L. Schiller, Ph. Fischbeck, L. Molitor, M. Krejca, T. Friedrich : “Evolutionary Minimization of Traffic Congestion”, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), Lille (en ligne), France, pp. 937-945, (Association for Computing Machinery) (2021)
  • B. Doerr, M. Krejca : “The Univariate Marginal Distribution Algorithm Copes Well With Deception and Epistasis”, Evolutionary Computation, vol. 29 (4), pp. 543-563, (Massachusetts Institute of Technology Press (MIT Press)) (2021)