MO-IOHinspector: Anytime Benchmarking of Multi-objective Algorithms Using IOHprofiler
D. Vermetten, J. Rook, O.L. Preuß, J. de Nobel, C. Doerr, M. López-Ibáñez, H. Trautmann, T. Bäck, in: H.K. Singh, T. Ray, J.D. Knowles, X. Li, J. Branke, B. Wang, A. Oyama (Eds.), Evolutionary Multi-Criterion Optimization - 13th International Conference, EMO 2025, Canberra, ACT, Australia, March 4-7, 2025, Proceedings, Part I, Springer, 2025, pp. 242–256.

Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single- and Multi-Objective Continuous Optimization Problems 
M. Seiler, P. Kerschke, H. Trautmann, Evolutionary Computation (2025) 1–27.

RandOptGen: A Unified Random Problem Generator for Single- and Multi-Objective Optimization Problems with Mixed-Variable Input Spaces
M. Seiler, O.L. Preuß, H. Trautmann, in: B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025, ACM, 2025, pp. 76–84.

Automated Algorithm Configuration and Systematic Benchmarking for Heterogeneous MNK-Landscapes
O.L. Preuß, C. Mensendiek, J. Rook, J. Bossek, H. Trautmann, in: B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025, ACM, 2025, pp. 58–66.

Deep reinforcement learning for instance-specific algorithm configuration (GECCO Best Paper Award)
E. Schede, M. Seiler, K. Tierney, H. Trautmann, in: B. Filipic (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025, ACM, 2025, pp. 1190–1198.

Efficient Online Automated Algorithm Selection in the Face of Data-Drift in Optimisation Problem Instances
J. Rook, Q. Renau, H. Trautmann, E. Hart, in: Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2025, Leiden, The Netherlands, August 27-29, 2025, ACM, 2025, pp. 262–272.

An Evolutionary Approach for the Computation of -Locally Optimal Solutions for Multi-Objective Multimodal Optimization
C. Hernández, A.E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2025) 1–1.

Exploratory Landscape Analysis for Mixed-Variable Problems
R.P. Prager, H. Trautmann, IEEE Transactions on Evolutionary Computation (2024) 1–1.

Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization
K. Dietrich, R. Prager, C. Doerr, H. Trautmann, in: M. Affenzeller, S. Winkler, A. Kononova, H. Trautmann, T. Tusar, P. Machado, T. Baeck (Eds.), Parallel Problem Solving from Nature — PPSN XVIII, Springer International Publishing, Cham, 2024, pp. 1–14.

Learned Features vs. Classical ELA on Affine BBOB Functions
M. Seiler, U. Skvorc, G. Cenikj, C. Doerr, H. Trautmann, in: M. Affenzeller, S. Winkler, A. Kononova, H. Trautmann, T. Tusar, P. Machado, T. Baeck (Eds.), Parallel Problem Solving from Nature — PPSN XVIII, Springer International Publishing, Cham, 2024, pp. 1–14.

On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems
O.L. Preuß, J. Rook, H. Trautmann, in: Applications of Evolutionary Computation, Springer Nature Switzerland, Cham, 2024.

Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP
M. Seiler, J. Rook, J. Heins, O.L. Preuß, J. Bossek, H. Trautmann, in: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2024.

Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection
M. Seiler, U. Skvorc, C. Doerr, H. Trautmann, in: P. Festa, D. Ferone, T. Pastore, O. Pisacane (Eds.), Learning and Intelligent Optimization - 18th International Conference, LION 18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers, Springer, 2024, pp. 361–376.

Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III
M. Affenzeller, S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado, T. Bäck, eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III, Springer, 2024.

Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part I
M. Affenzeller, S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado, T. Bäck, eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part I, Springer, 2024.

Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV
M. Affenzeller, S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado, T. Bäck, eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV, Springer, 2024.

Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features
R.P. Prager, K. Dietrich, L. Schneider, L. Schäpermeier, B. Bischl, P. Kerschke, H. Trautmann, O. Mersmann, in: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2023, pp. 129–139.

Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features
R.P. Prager, H. Trautmann, in: J. Correia, S. Smith, R. Qaddoura (Eds.), Applications of Evolutionary Computation, Springer Nature Switzerland, Cham, 2023, pp. 411–425.

Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets
L. Schäpermeier, P. Kerschke, C. Grimme, H. Trautmann, in: M. Emmerich, A. Deutz, H. Wang, A.V. Kononova, B. Naujoks, K. Li, K. Miettinen, I. Yevseyeva (Eds.), Evolutionary Multi-Criterion Optimization, Springer Nature Switzerland, Cham, 2023, pp. 291–304.

Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python
R.P. Prager, H. Trautmann, Evolutionary Computation (2023) 1–25.