Publications

2025

• Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization ProblemsSeiler, M. V., Kerschke, P. & Trautmann, H., 2025, In: Evolutionary Computation. p. 1-27, 27 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article

2024

• Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal OptimizationRodriguez-Fernandez, A. E., Schäpermeier, L., Hernández, C., Kerschke, P., Trautmann, H. & Schütze, O., 11 Sep 2024, In: IEEE transactions on evolutionary computation : a publication of the IEEE Neural Networks CouncilElectronic (full-text) versionResearch output: Contribution to journal > Research article

2023

• Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for GamesVolz, V., Naujoks, B., Kerschke, P. & Tušar, T., Mar 2023, In: Applied soft computing : the official journal of the World Federation on Soft Computing (WFSC). 136, 110121Electronic (full-text) versionResearch output: Contribution to journal > Research article
• A study on the effects of normalized TSP features for automated algorithm selectionHeins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H. & Kerschke, P., Jan 2023, In: Theoretical computer science : the journal of the EATCS. 940, B, p. 123-145, 23 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article

2022

• Plotting Impossible? Surveying Visualization Methods for Continuous Multi-Objective Benchmark ProblemsSchäpermeier, L., Grimme, C. & Kerschke, P., Dec 2022, In: IEEE transactions on evolutionary computation : a publication of the IEEE Neural Networks Council. 26, 6, p. 1306-1320, 15 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
• Process-Oriented Stream Classification Pipeline: A Literature ReviewClever, L., Pohl, J. S., Bossek, J., Kerschke, P. & Trautmann, H., 9 Sep 2022, In: Applied sciences. 12, 18, 9094Electronic (full-text) versionResearch output: Contribution to journal > Review article
• The objective that freed me: a multi-objective local search approach for continuous single-objective optimizationAspar, P., Steinhoff, V., Schäpermeier, L., Kerschke, P., Trautmann, H. & Grimme, C., 5 Sep 2022, In: Natural computing : an innovative journal bridging biosciences and computer sciences ; an international journal. 22, 2, p. 271 - 285, 15 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
• Estimation of component reliability from superposed renewal processes by means of latent variablesRodrigues, A., Kerschke, P., Pereira, C. A. D. B., Trautmann, H., Wagner, C., Hellingrath, B. & Polpo, A., Mar 2022, In: Computational statistics. 37, 1, p. 355–379, 25 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article

2021

• Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimizationGrimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H. & 1 others, Dec 2021, In: Computers and Operations Research. 136, 105489Electronic (full-text) versionResearch output: Contribution to journal > Research article

2025

• Greedy Restart Schedules: A Baseline for Dynamic Algorithm Selection on Numerical Black-box Optimization Problems.Schäpermeier, L., Jul 2025, GECCO '25: Proceedings of the Genetic and Evolutionary Computation Conference. p. 1199 - 1207Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Clearing the Combinatorial Fog: Tracing the Hidden Paths of TSP HeuristicsHeins, J., Dengel, S., Whitley, D. & Kerschke, P., 27 Jun 2025, Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic AlgorithmsResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAXHeins, J., Whitley, D. & Kerschke, P., 19 Mar 2025, Proceedings of the Genetic and Evolutionary Computation ConferenceResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Efficient Flat Yard Shunting via Instance-Aware OptimizationBodi, L. M., Rauschert, F., Krauth, M. & Kerschke, P., 2025Research output: Contribution to conferences > Presentation slides
• Size matters: Adapting HEROS to ensure usability in large flat yardsRauschert, F., Bodi, L. M., Krauth, M. & Kerschke, P., 2025Research output: Contribution to conferences > Poster

2024

• Optimizing Rail Shunting Operations through Multi-Stage AI HeuristicsRauschert, F., Bodi, L. M. & Krauth, M., 20 Oct 2024Research output: Contribution to conferences > Presentation slides
• Physical Layer Security: Learning-Aided Attack Detection based on 5G NR SRSNinnemann, J., Rauschert, F., Schwarzbach, P., Kerschke, P. & Michler, O., 30 Sep 2024, 2024 IEEE Conference on Communications and Network Security (CNS). p. 1-6Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Dancing to the State of the Art?: How Candidate Lists Influence LKH for Solving the Traveling Salesperson ProblemHeins, J., Schäpermeier, L., Kerschke, P. & Whitley, D., 7 Sep 2024, Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part I. Affenzeller, M., Winkler, S. M., Kononova, A. V., Bäck, T., Trautmann, H., Tušar, T. & Machado, P. (eds.).p. 100-115, 16 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box OptimizationDietrich, K., Prager, R. P., Doerr, C. & Trautmann, H., 7 Sep 2024, Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part II. Affenzeller, M., Winkler, S. M., Kononova, A. V., Bäck, T., Trautmann, H., Tušar, T. & Machado, P. (eds.).p. 154–169, 16 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Reinvestigating the R2 Indicator: Achieving Pareto Compliance by IntegrationSchäpermeier, L. & Kerschke, P., 7 Sep 2024, Parallel Problem Solving from Nature – PPSN XVIII: 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14–18, 2024, Proceedings, Part IV. Affenzeller, M., Winkler, S. M., Kononova, A. V., Bäck, T., Trautmann, H., Tušar, T. & Machado, P. (eds.).p. 202-216, 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box OptimizationDietrich, K., Vermetten, D., Doerr, C. & Kerschke, P., 14 Jul 2024, Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery (ACM), p. 1007 - 1016, 10 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Enhancing Emergency Response Efficiency via Deep Reinforcement Learning: A Novel Model for Dynamic DispatchingRauschert, F., Ribesmeier, M. & Kerschke, P., 2024Research output: Contribution to conferences > Presentation slides

2023

• Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape FeaturesPrager, R. P., Dietrich, K., Schneider, L., Schäpermeier, L., Bischl, B., Kerschke, P., Trautmann, H. & 1 others, 30 Aug 2023, FOGA '23: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. p. 129-139, 11 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking SuiteDietrich, K. & Kerschke, P., 15 Jul 2023, GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion. 4 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• GECCO 2023 Tutorial: Exploratory Landscape AnalysisKerschke, P. & Preuss, M., 15 Jul 2023, GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation. p. 990–1007, 18 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto SetsSchäpermeier, L., Kerschke, P., Grimme, C. & Trautmann, H., 2023, Evolutionary Multi-Criterion Optimization - 12th International Conference, EMO 2023, Proceedings. Emmerich, M., Deutz, A., Wang, H., Kononova, A. V., Naujoks, B., Li, K., Miettinen, K. & Yevseyeva, I. (eds.).14 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2022

• Mixture of Decision Trees for Interpretable Machine LearningBrüggenjürgen, S., Schaaf, N., Kerschke, P. & Huber, M. F., Dec 2022, Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022. Wani, M. A., Kantardzic, M., Palade, V., Neagu, D., Yang, L. & Chan, K. (eds.).p. 1175-1182, 8 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapesSeiler, M. V., Prager, R. P., Kerschke, P. & Trautmann, H., 8 Jul 2022, GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. p. 657-665, 9 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• MOLE: Digging Tunnels Through Multimodal Multi-objective LandscapesSchäpermeier, L., Grimme, C. & Kerschke, P., 8 Jul 2022, GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. p. 592-600, 9 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis MethodsPrager, R. P., Seiler, M. V., Trautmann, H. & Kerschke, P., 2022, Parallel Problem Solving from Nature – PPSN XVII - 17th International Conference, PPSN 2022, Proceedings. Rudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T. (eds.).p. 3-17, 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization ProblemsHeins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J. & Trautmann, H., 2022, Parallel Problem Solving from Nature – PPSN XVII - 17th International Conference, PPSN 2022, Proceedings. Rudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T. (eds.).p. 192-206, 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• HPO × ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape AnalysisSchneider, L., Schäpermeier, L., Prager, R. P., Bischl, B., Trautmann, H. & Kerschke, P., 2022, Parallel Problem Solving from Nature – PPSN XVII - 17th International Conference, PPSN 2022, Proceedings. Rudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T. (eds.).p. 575-589, 15 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• Increasing the Diversity of Benchmark Function Sets Through Affine RecombinationDietrich, K. & Mersmann, O., 2022, Parallel Problem Solving from Nature – PPSN XVII - 17th International Conference, PPSN 2022, Proceedings. Rudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T. (eds.).p. 590-602, 13 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2021

• Towards Feature-Free Automated Algorithm Selection for Single-Objective Continuous Black-Box OptimizationPrager, R. P., Seiler, M. V., Trautmann, H. & Kerschke, P., 5 Dec 2021, 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - ProceedingsElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
• On the potential of normalized TSP features for automated algorithm selectionHeins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H. & Kerschke, P., 6 Sep 2021, FOGA 2021 - Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic AlgorithmsElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution

2022

• Parallel Problem Solving from Nature – PPSN XVII: 17th International Conference, PPSN 2022, Dortmund, Germany, September 10–14, 2022, Proceedings, Part IRudolph, G., Kononova, A. V., Aguirre, H., Kerschke, P., Ochoa, G. & Tušar, T., 2022, Springer, ChamElectronic (full-text) versionResearch output: Book/Report/Anthology > Monograph

2025

• Efficient Flat Yard Shunting via Instance-Aware OptimizationBodi, L. M., Rauschert, F., Krauth, M. & Kerschke, P., 2025Research output: Contribution to conferences > Presentation slides
• Size matters: Adapting HEROS to ensure usability in large flat yardsRauschert, F., Bodi, L. M., Krauth, M. & Kerschke, P., 2025Research output: Contribution to conferences > Poster

2024

• Optimizing Rail Shunting Operations through Multi-Stage AI HeuristicsRauschert, F., Bodi, L. M. & Krauth, M., 20 Oct 2024Research output: Contribution to conferences > Presentation slides
• Enhancing Emergency Response Efficiency via Deep Reinforcement Learning: A Novel Model for Dynamic DispatchingRauschert, F., Ribesmeier, M. & Kerschke, P., 2024Research output: Contribution to conferences > Presentation slides

2021

• Lifting the Multimodality-Fog in Continuous Multi-objective OptimizationKerschke, P. & Grimme, C., 2021, Natural Computing Series. p. 89-111, 23 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Chapter in book/Anthology/Report