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

Performance Management Approach for Digital Platforms in B Markets
L. Özcan, L. 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.

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.

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.

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).

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.

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.

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.

Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints
B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, Production Engineering 14 (2020) 417–423.

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).