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.

Interview Study on Strategy Options for Platform Operation in B Markets
L. Özcan, T. Fichtler, B. Kasten, C. Koldewey, R. Dumitrescu, in: 2023.

Why do Digital Platforms succeed or fail? - A Literature Review on Success and Failure Factors
L. Özcan, C. Koldewey, E. Duparc, H. van der Valk, B. Otto, R. Dumitrescu, in: 2022.

A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement
Y. Shi, S. Harzheim, M. Hofmann, T. Wallmersperger, in: Material Modeling and Structural Mechanics, Springer International Publishing, Cham, 2022.

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.

Performance Management Approach for Digital Platforms in B Markets
L. Özcan, L.I. Kirchberg, C. Koldewey, R. Dumitrescu, in: I. Bitran, L. Bitetti, S.  Conn, J. Fishburn, E. Huizingh, M. Torkkeli, J. Yang (Eds.), The Role of Innovation: Past, Present, Future, Athens, 2022.

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.

AutoML for Multi-Label Classification: Overview and Empirical Evaluation
M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.

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).

DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning
S.B. Schneider, H. Karl, R. Khalili, A. Hecker, DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning, 2021.

A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions
A. Bender, Machines 9 (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.

Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers
D. Beverungen, D. Kundisch, N. Wünderlich, Journal of Service Management 32 (2021) 507–532.

Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties
A. Bender, W. Sextro, in: P. Do, S. King,  Olga Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021, 2021.

The Online Multi-Commodity Facility Location Problem
J. Castenow, B. Feldkord, T. Knollmann, M. Malatyali, F. Meyer auf der Heide, in: Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures, 2020.

5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services
D. Camps-Mur, F.  Canellas, A. Machwe, J. Paracuellos, K. Choumas, D. Giatsios, T. Korakis, H. Razzaghi Kouchaksaraei, in: The 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020), n.d.

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).

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.