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Publikationen

2025

A First Runtime Analysis of the PAES-25: An Enhanced Variant of the Pareto Archived Evolution Strategy

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 , New York, NY, USA: ACM, 2025. pp. 202-213.

DOI: \url10.1145/3729878.3746618

ISBN: 9798400718595

A Many-Objective Problem Where Crossover is Provably Indispensable

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.

DOI: \url10.1145/3712255.3734223

ISBN: 9798400714641

A Royal Road Function for Permutation Spaces: an Example Where Order Crossover is Provably Essential

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.

DOI: \url10.1145/3712256.3726403

ISBN: 9798400714658

Achieving Tight Runtime Bounds on Jumpk by Proving that Genetic Algorithms Evolve Near-Maximal Population Diversity

A. Opris, J. Lengler and D. Sudholt, "Achieving Tight Runtime Bounds on Jumpk by Proving that Genetic Algorithms Evolve Near-Maximal Population Diversity" , Algorithmica , 2025.

DOI: \url10.1007/s00453-025-01323-x

Analysing the Effectiveness of Mutation Operators for One-Sided Bipartite Crossing Minimisation

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.

DOI: \url10.1145/3712256.3726407

ISBN: 9798400714658

Empirical Linkage Learning Provably Builds Truthful Models on Concatenated Traps and H-IFF

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.

DOI: \url10.1145/3712256.3726417

ISBN: 9798400714658

Runtime Analysis of Functions Where Widely-Used Evolutionary Multi-Objective Algorithms Beat Simple Ones

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: \url10.1145/3732793

ISBN: 9798400714658

The Compact Genetic Algorithm Struggles on Cliff Functions

F. Neumann, D. Sudholt and C. Witt, "The Compact Genetic Algorithm Struggles on Cliff Functions" , Algorithmica , vol. 87, no. 4, pp. 507-536, 2025.

DOI: \url10.1007/S00453-024-01281-W

Tight Runtime Guarantees From Understanding the Population Dynamics of the GSEMO Multi-Objective Evolutionary Algorithm

B. Doerr, M. Krejca and A. Opris, Tight Runtime Guarantees From Understanding the Population Dynamics of the GSEMO Multi-Objective Evolutionary Algorithm , 2025.

2024

A Tight Runtime Bound for a GA on Jump_k for Realistic Crossover Probabilities

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.

DOI: 10.1145/3638529.3654120

Datei: https://doi.org/10.1145/3638529.3654120

Analysing Equilibrium States for Population Diversity

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

Crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation

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

Empirical Evaluation of Evolutionary Algorithms with Power-Law Ranking Selection

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.

DOI: 10.1007/978-3-031-57808-3\_16

Datei: https://doi.org/10.1007/978-3-031-57808-3\_16

Evolutionary Computation Meets Graph Drawing: Runtime Analysis for Crossing Minimisation on Layered Graph Drawings

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

Datei: https://doi.org/10.1145/3638529.3654105

Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions

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

Datei: https://doi.org/10.1145/3638529.3654160

Hot of the Press: Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation

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

Datei: https://doi.org/10.1145/3638530.3664057

Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis

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

ISBN: 9798400704949

Level-Based Theorems for Runtime Analysis of Multi-objective Evolutionary Algorithms

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

Datei: https://doi.org/10.1007/978-3-031-70071-2_16

On the Equivalence Between Stochastic Tournament and Power-Law Ranking Selection and How to Implement Them Efficiently

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

Datei: https://doi.org/10.1007/978-3-031-70071-2_15

Runtime Analyses of NSGA-III on Many-Objective Problems

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

Datei: https://doi.org/10.1145/3638529.3654218

Self-adjusting offspring population sizes outperform fixed parameters on the cliff function

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

Self-adjusting Population Sizes for Non-elitist Evolutionary Algorithms: Why Success Rates Matter

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

Datei: https://doi.org/10.1007/s00453-023-01153-9

The Compact Genetic Algorithm Struggles on Cliff Functions

F. Neumann, D. Sudholt and C. Witt, "The Compact Genetic Algorithm Struggles on Cliff Functions" , Algorithmica , 2024.

DOI: 10.1007/s00453-024-01281-w

2023

A Proof That Using Crossover Can Guarantee Exponential Speed-Ups in Evolutionary Multi-Objective Optimisation

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

Datei: https://doi.org/10.1609/aaai.v37i10.26460

Analysing Equilibrium States for Population Diversity

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

Datei: https://doi.org/10.1145/3583131.3590465

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