Publications

A. Opris, J. Lengler and D. Sudholt, "A Tight O(4^k/p_c) Runtime Bound for a (\mu+1)GA on Jump_k for Realistic Crossover Probabilities" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 , Xiaodong Li and Julia Handl, Eds. ACM , 2024.
DOI: 10.1145/3638529.3654120
https://doi.org/10.1145/3638529.3654120

J. Lengler, A. Opris and D. Sudholt, "Analysing Equilibrium States for Population Diversity" , Algorithmica , vol. 86 , no. 7 , pp. 1-35 , 2024.
DOI: 10.1007/s00453-024-01226-3

D. Dang, A. Opris and D. Sudholt, "Crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation" , Artificial Intelligence , vol. 330 , pp. 104098 , 2024.
DOI: 10.1016/j.artint.2024.104098

J. Baumann, I. Rutter and D. Sudholt, "Evolutionary Computation Meets Graph Drawing: Runtime Analysis for Crossing Minimisation on Layered Graph Drawings" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 , Xiaodong Li and Julia Handl, Eds. ACM , 2024.
DOI: 10.1145/3638529.3654105
https://doi.org/10.1145/3638529.3654105

M. Schmidbauer, A. Opris, J. Bossek, F. Neumann and D. Sudholt, "Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 , Xiaodong Li and Julia Handl, Eds. ACM , 2024.
DOI: 10.1145/3638529.3654160
https://doi.org/10.1145/3638529.3654160

A. Opris, D. Dang and D. Sudholt, "Hot of the Press: Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation" in Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 , Xiaodong Li and Julia Handl, Eds. ACM , 2024. pp. 51-52.
DOI: 10.1145/3638530.3664057
https://doi.org/10.1145/3638530.3664057

D. Dang, A. Opris and D. Sudholt, "Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis" in Proceedings of the Genetic and Evolutionary Computation Conference , Li, Xiaodong and Handl, Julia, Eds. New York, NY, USA : ACM , 2024. pp. 484-492.
DOI: 10.1145/3638529.3654177

D. Dang, A. Opris and D. Sudholt, "Level-Based Theorems for Runtime Analysis of Multi-objective Evolutionary Algorithms" in Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III , Michael Affenzeller and Stephan M. Winkler and Anna V. Kononova and Heike Trautmann and Tea Tusar and Penousal Machado and Thomas Bäck, Eds. Springer , 2024. pp. 246-263.
DOI: 10.1007/978-3-031-70071-2_16
https://doi.org/10.1007/978-3-031-70071-2_16

D. Dang, A. Opris and D. Sudholt, "On the Equivalence Between Stochastic Tournament and Power-Law Ranking Selection and How to Implement Them Efficiently" in Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III , Michael Affenzeller and Stephan M. Winkler and Anna V. Kononova and Heike Trautmann and Tea Tusar and Penousal Machado and Thomas Bäck, Eds. Springer , 2024. pp. 230-245.
DOI: 10.1007/978-3-031-70071-2_15
https://doi.org/10.1007/978-3-031-70071-2_15

A. Opris, D. Dang, F. Neumann and D. Sudholt, "Runtime Analyses of NSGA-III on Many-Objective Problems" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 , Xiaodong Li and Julia Handl, Eds. ACM , 2024.
DOI: 10.1145/3638529.3654218
https://doi.org/10.1145/3638529.3654218

M. A. Hevia Fajardo and D. Sudholt, "Self-adjusting offspring population sizes outperform fixed parameters on the cliff function" , Artificial Intelligence , vol. 328 , pp. 104061 , 2024.
DOI: 10.1016/j.artint.2023.104061

M. A. H. Fajardo and D. Sudholt, "Self-adjusting Population Sizes for Non-elitist Evolutionary Algorithms: Why Success Rates Matter" , Algorithmica , vol. 86 , no. 2 , pp. 526-565 , 2024.
DOI: 10.1007/S00453-023-01153-9
https://doi.org/10.1007/s00453-023-01153-9

F. Neumann, D. Sudholt and C. Witt, "The Compact Genetic Algorithm Struggles on Cliff Functions" , Algorithmica , 2024.
DOI: 10.1007/s00453-024-01281-w

D. Dang, A. Opris, B. Salehi and D. Sudholt, "A Proof That Using Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation" in Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023 , Brian Williams and Yiling Chen and Jennifer Neville, Eds. AAAI Press , 2023. pp. 12390-12398.
DOI: 10.1609/AAAI.V37I10.26460
https://doi.org/10.1609/aaai.v37i10.26460

J. Lengler, A. Opris and D. Sudholt, "Analysing Equilibrium States for Population Diversity" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023 , Sara Silva and Lu\'\is Paquete, Eds. ACM , 2023. pp. 1628-1636.
DOI: 10.1145/3583131.3590465
https://doi.org/10.1145/3583131.3590465

D. Dang, A. Opris, B. Salehi and D. Sudholt, "Analysing the Robustness of NSGA-II under Noise" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023 , Sara Silva and Lu\'\is Paquete, Eds. ACM , 2023. pp. 642-651.
DOI: 10.1145/3583131.3590421
https://doi.org/10.1145/3583131.3590421

J. Jorritsma, J. Lengler and D. Sudholt, "Comma Selection Outperforms Plus Selection on OneMax with Randomly Planted Optima" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023 , Sara Silva and Lu\'\is Paquete, Eds. ACM , 2023. pp. 1602-1610.
DOI: 10.1145/3583131.3590488
https://doi.org/10.1145/3583131.3590488

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" in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023 , Sara Silva and Lu\'\is Paquete, Eds. ACM , 2023. pp. 1546-1554.
DOI: 10.1145/3583131.3590383
https://doi.org/10.1145/3583131.3590383

C. Kneissl and D. Sudholt, "The Cost of Randomness in Evolutionary Algorithms: Crossover can Save Random Bits" in Evolutionary Computation in Combinatorial Optimization - 23rd European Conference, EvoCOP 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12-14, 2023, Proceedings , Leslie P\'erez C\'aceres and Thomas St\"utzle, Eds. Springer , 2023. pp. 179-194.
DOI: 10.1007/978-3-031-30035-6\_12
https://doi.org/10.1007/978-3-031-30035-6\_12

D. Sudholt and G. Squillero, "Theory and Practice of Population Diversity in Evolutionary Computation" in Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023 , Sara Silva and Lu\'\is Paquete, Eds. ACM , 2023. pp. 1361-1378.
DOI: 10.1145/3583133.3595053
https://doi.org/10.1145/3583133.3595053

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 .