Publications

J. Lengler, A. Opris and D. Sudholt, "Analysing Equilibrium States for Population Diversity" in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2023) , ACM , 2023 .

D. Dang, A. Opris, B. Salehi and D. Sudholt, "Analysing the Robustness of NSGA-II under Noise" , 2023 .

J. Jorritsma, J. Lengler and D. Sudholt, "Comma Selection Outperform Plus Selection on OneMax with Randomly Planted Optima" , 2023 .

J. Bossek and D. Sudholt, "Do additional target points speed up evolutionary algorithms?" , Theoretical Computer Science , vol. 950 , pp. 113757 , 2023.
DOI: 10.1016/j.tcs.2023.113757

J. Bossek and D. Sudholt, "Runtime Analysis of Quality Diversity Algorithms" , 2023 .

C. Kneissl and D. Sudholt, The Cost of Randomness in Evolutionary Algorithms: Crossover can Save Random Bits. .... 2023.
DOI: 10.1007/978-3-031-30035-6\textunderscore 12

V. D. Bhuva, D. Dang, L. Huber and D. Sudholt, "Evolutionary Algorithms for Cardinality-Constrained Ising Models" , 2022.
DOI: 10.1007/978-3-031-14721-0$\backslash$\textunderscore 32

M. A. H. Fajardo and D. Sudholt, "Hard problems are easier for success-based parameter control" , pp. 796-804 , 2022.
DOI: 10.1145/3512290.3528781

G. T. Hall, D. Sudholt and P. S. Oliveto, "On the impact of the performance metric on efficient algorithm configuration" , Nov. 2022. http://1. https://www.sciencedirect.com/science/article/abs/pii/S0004370221001806 .

E. Covantes Osuna and D. Sudholt, "Runtime Analysis of Restricted Tournament Selection for Bimodal Optimisation" , Evolutionary Computation , 2022. MIT Press .

F. Neumann, D. Sudholt and C. Witt, "The compact genetic algorithm struggles on Cliff functions" , pp. 1426-1433 , 2022.
DOI: 10.1145/3512290.3528776

M. A. Hevia Fajardo and D. Sudholt, "Theoretical and Empirical Analysis of Parameter Control Mechanisms in the (1 + (\textgreekl, \textgreekl)) Genetic Algorithm" , ACM Transactions on Evolutionary Learning and Optimization , vol. 2 , no. 4 , pp. 1-39 , 2022.
DOI: 10.1145/3564755

D. Sudholt and G. Squillero, "Theory and practice of population diversity in evolutionary computation" , pp. 975-992 , 2022.
DOI: 10.1145/3377929.3389892

P. S. Oliveto, D. Sudholt and C. Witt, "Tight Bounds on the Expected Runtime of a Standard Steady State Genetic Algorithm", Algorithmica" , 2022.

D. Sudholt, "Analysing the Robustness of Evolutionary Algorithms to Noise: Refined Runtime Bounds and an Example Where Noise is Beneficial" , Algorithmica , vol. 83 , no. 4 , pp. 976-1011 , 2021.
https://doi.org/10.1007/s00453-020-00671-0

J. Bossek and D. Sudholt, "Do additional optima speed up evolutionary algorithms?" in Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms , Finck, Steffen and Hellwig, Michael and Oliveto, Pietro S., Eds. New York, NY, USA : ACM , 2021. pp. 1--11.
DOI: 10.1145/3450218.3477309

M. A. Hevia Fajardo and D. Sudholt, "Self-adjusting offspring population sizes outperform fixed parameters on the cliff function" in Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms , Finck, Steffen and Hellwig, Michael and Oliveto, Pietro S., Eds. New York, NY, USA : ACM , 2021. pp. 1--15.
DOI: 10.1145/3450218.3477306

M. A. Hevia Fajardo and D. Sudholt, "Self-Adjusting Population Sizes for Non-Elitist Evolutionary Algorithms: Why Success Rates Matter" in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2021) , ACM , 2021.

J. Lengler, D. Sudholt and C. Witt, "The Complex Parameter Landscape of the Compact Genetic Algorithm" , Algorithmica , vol. 83 , no. 4 , pp. 1096-1137 , 2021. https://rdcu.be/b9KBR .

J. Bossek, F. Neumann, P. Peng and D. Sudholt, "Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem" , Algorithmica , 2021.
DOI: 10.1007/s00453-021-00838-3

P. S. Oliveto, D. Sudholt and C. Witt, "A Tight Lower Bound on the Expected Runtime of Standard Steady State Genetic Algorithms" in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020) , ACM , 2020. pp. 1323-1331.
https://doi.org/10.1145/3377930.3390212

G. T. Hall, P. S. Oliveto and D. Sudholt, "Analysis of the Performance of Algorithm Configurators for Search Heuristics with Global Mutation Operators" in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020) , ACM , 2020. pp. 823-831.
https://doi.org/10.1145/3377930.3390218

N. Albunian, G. Fraser and D. Sudholt, "Causes and Effects of Fitness Landscapes in Unit Test Generation" in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020) , ACM , 2020. pp. 1204-1212.
https://doi.org/10.1145/3377930.3390194

E. Covantes Osuna, W. Gao, F. Neumann and D. Sudholt, "Design and Analysis of Diversity-Based Parent Selection Schemes for Speeding Up Evolutionary Multi-objective Optimisation" , Theoretical Computer Science , vol. 832 , pp. 123-142 , 2020.
https://authors.elsevier.com/c/1b6NN15DaHylEh

M. Foster, M. Hughes, G. O'Brien, P. S. Oliveto, J. Pyle, D. Sudholt and J. Williams, "Do Sophisticated Evolutionary Algorithms Perform Better than Simple Ones?" in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020) , ACM , 2020. pp. 184-192.
https://doi.org/10.1145/3377930.3389830