Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems
O. Schön, R.-S. Götte, J. Timmermann, in: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 2022, pp. 19–24.

BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems
J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 192–206.

On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems
J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359.

Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning
S.B. Schneider, R. Khalili, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, A. Hecker, Transactions on Network and Service Management (2021).

Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization
C. Grimme, P. Kerschke, P. Aspar, H. Trautmann, M. Preuss, A.H. Deutz, H. Wang, M. Emmerich, Computers &; Operations Research 136 (2021) 105489.

A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms
J. Bossek, P. Kerschke, H. Trautmann, Applied Soft Computing 88 (2020) 105901.

Dynamic Bi-Objective Routing of Multiple Vehicles
J. Bossek, C. Grimme, H. Trautmann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 166–174.

A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms
J. Bossek, P. Kerschke, H. Trautmann, Applied Soft Computing 88 (2020).

Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: K. Deb, E. Goodman, C.A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO), Springer International Publishing, Cham, 2019, pp. 516–528.

On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem
J. Bossek, C. Grimme, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2019, pp. 516–523.