MO-SMAC: Multi-objective Sequential Model-based Algorithm Configuration
J.G. Rook, C. Benjamins, J. Bossek, H. Trautmann, H.H. Hoos, M. Lindauer, Evolutionary Computation (2025) 1–25.

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.

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.

Multi-objective Ranking using Bootstrap Resampling
J. Rook, H.H. Hoos, H. Trautmann, in: X. Li, J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024, ACM, 2024, pp. 155–158.

Finding ?5-Locally Optimal Solutions for Multi-Objective Multimodal Optimization
A.E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2024) 1–1.

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.

Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part II
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 II, Springer, 2024.

On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems
O.L. Preuß, J. Rook, H. Trautmann, in: S.L. Smith, J. Correia, C. Cintrano (Eds.), Applications of Evolutionary Computation - 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3-5, 2024, Proceedings, Part I, Springer, 2024, pp. 305–321.

Learned Features vs. Classical ELA on Affine BBOB Functions
M. Seiler, U. Skvorc, G. Cenikj, C. Doerr, H. Trautmann, in: 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 II, Springer, 2024, pp. 137–153.