A. Opris, "A First Runtime Analysis of NSGA-III on a Many-Objective Multimodal Problem: Provable Exponential Speedup via Stochastic Population Update" in Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , Kwok, James and Zilberstein, Shlomo, Eds. California: International Joint Conferences on Artificial Intelligence Organization, 2025. pp. 8903-8911.
ISBN: 978-1-956792-06-5
A. Opris, "A First Runtime Analysis of the PAES-25: An Enhanced Variant of the Pareto Archived Evolution Strategy" in Proceedings of the Foundations of Genetic Algorithms XVIII on ZZZ , Filipic, Bogdan and Ochoa, Gabriela, Eds. New York, NY, USA: ACM, 2025. pp. 202-213.
ISBN: 9798400718595
A. Opris, "A Many-Objective Problem Where Crossover is Provably Indispensable" in Proceedings of the Genetic and Evolutionary Computation Conference Companion , Filipič, Bogdan and Ochoa, Gabriela, Eds. New York, NY, USA: ACM, 2025. pp. 49-50.
ISBN: 9798400714641
A. Opris, "A Many-Objective Problem Where Crossover Is Provably Indispensable" , Proceedings of the AAAI Conference on Artificial Intelligence , vol. 39, no. 25, pp. 27108-27116, 2025. ACM.
DOI: 10.1609/aaai.v39i25.34918
ISBN: 9798400714641
A. Opris, S. Sonntag and D. Sudholt, "A Royal Road Function for Permutation Spaces: an Example Where Order Crossover is Provably Essential" in Proceedings of the Genetic and Evolutionary Computation Conference , Filipic, Bogdan and Ochoa, Gabriela, Eds. New York, NY, USA: ACM, 2025. pp. 1631-1640.
ISBN: 9798400714658
A. Opris, J. Lengler and D. Sudholt, "Achieving Tight Runtime Bounds on Jumpk by Proving that Genetic Algorithms Evolve Near-Maximal Population Diversity" , Algorithmica , no. 11, pp. 1564-1619, 2025. ACM.
DOI: 10.1007/s00453-025-01323-x
ISBN: 9798400718595
J. Baumann, I. Rutter and D. Sudholt, "Analysing the Effectiveness of Mutation Operators for One-Sided Bipartite Crossing Minimisation" in Proceedings of the Genetic and Evolutionary Computation Conference , Filipic, Bogdan and Ochoa, Gabriela, Eds. New York, NY, USA: ACM, 2025. pp. 872-880.
ISBN: 9798400714658
M. Schmidbauer and D. Sudholt, "Empirical Linkage Learning Provably Builds Truthful Models on Concatenated Traps and H-IFF" in Proceedings of the Genetic and Evolutionary Computation Conference , Filipic, Bogdan and Ochoa, Gabriela, Eds. New York, NY, USA: ACM, 2025. pp. 827-835.
ISBN: 9798400714658
D. Dang, A. Opris and D. Sudholt, "Runtime Analysis of Functions Where Widely-Used Evolutionary Multi-Objective Algorithms Beat Simple Ones" , ACM Transactions on Evolutionary Learning and Optimization , pp. 1604-1612, 2025. ACM.
DOI: 10.1145/3732793
ISBN: 9798400714658
F. Neumann, D. Sudholt and C. Witt, "The Compact Genetic Algorithm Struggles on Cliff Functions" , Algorithmica , vol. 87, no. 4, pp. 507-536, 2025.
D. Dang, A. Neumann, F. Neumann, A. Opris and D. Sudholt, "Theoretical Analysis of Evolutionary Algorithms with Quality Diversity for a Classical Path Planning Problem" in Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , Kwok, James and Zilberstein, Shlomo, Eds. California: International Joint Conferences on Artificial Intelligence Organization, 2025. pp. 8858-8866.
ISBN: 978-1-956792-06-5
B. Doerr, M. S. Krejca and A. Opris, "Tight Runtime Guarantees From Understanding the Population Dynamics of the GSEMO Multi-Objective Evolutionary Algorithm" in Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , Kwok, James and Zilberstein, Shlomo, Eds. California: International Joint Conferences on Artificial Intelligence Organization, 2025. pp. 8876-8884.
ISBN: 978-1-956792-06-5
D. Dang, A. Opris and D. Sudholt, "Why Dominance Is Not Enough: Lessons from Practical Evolutionary Multi-Objective Algorithms" in Proceedings of the Genetic and Evolutionary Computation Conference , Filipic, Bogdan and Ochoa, Gabriela, Eds. New York, NY, USA: ACM, 2025. pp. 1604-1612.
ISBN: 9798400714658
A. Opris, J. Lengler and D. Sudholt, "A Tight Runtime Bound for a 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.
J. Lengler, A. Opris and D. Sudholt, "Analysing Equilibrium States for Population Diversity" , Algorithmica , vol. 86, no. 7, pp. 1-35, 2024.
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.
D. Dang, A. V. Eremeev and X. Qin, "Empirical Evaluation of Evolutionary Algorithms with Power-Law Ranking Selection" in Intelligent Information Processing XII - 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3-6, 2024, Proceedings, Part I , Zhongzhi Shi and Jim T\orresen and Shengxiang Yang, Eds. Springer, 2024. pp. 217-232.
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.
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.
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.
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.
ISBN: 9798400704949
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.
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.
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.
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.
