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.

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.

On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem
J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2023, pp. 248–256.

Runtime Analysis of Quality Diversity Algorithms
J. Bossek, D. Sudholt, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2023, pp. 1546–1554.

Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space
A. Marrero, E. Segredo, E. Hart, J. Bossek, A. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2023, pp. 312–320.

Do Additional Target Points Speed Up Evolutionary Algorithms?
J. Bossek, D. Sudholt, Theoretical Computer Science (2023) 113757.

On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem
J. Bossek, C. Grimme, Evolutionary Computation (2023) 1–35.