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Özcan, L., Kirchberg, L., Koldewey, C., &; Dumitrescu, R. (2022). Performance Management Approach for Digital Platforms in B Markets. In I. Bitran, L. Bitetti, S.  Conn, J. Fishburn, E. Huizingh, M. Torkkeli, &; J. Yang (Eds.), The Role of Innovation: Past, Present, Future.
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Özcan, L., Koldewey, C., Duparc, E., van der Valk, H., Otto, B., &; Dumitrescu, R. (2022). Why do Digital Platforms succeed or fail? - A Literature Review on Success and Failure Factors. 28th Americas Conference on Information Systems (AMCIS), Minneapolis.
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Shi, Y., Harzheim, S., Hofmann, M., &; Wallmersperger, T. (2022). A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement. In Material Modeling and Structural Mechanics. Springer International Publishing.https://doi.org/10.1007/978-3-030-97675-0_9 
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Schön, O., Götte, R.-S., &; Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55(12), 19–24.https://doi.org/10.1016/j.ifacol.2022.07.282 
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Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., &; Trautmann, H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &; T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp. 192–206). Springer International Publishing.https://doi.org/10.1007/978-3-031-14714-2_14 
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Rook, J., Trautmann, H., Bossek, J., &; Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359.https://doi.org/10.1145/3520304.3528998 
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Wever, M. D., Tornede, A., Mohr, F., &; Hüllermeier, E. (2021). AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–1.https://doi.org/10.1109/tpami.2021.3051276 
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Schneider, S. B., Khalili, R., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., &; Hecker, A. (2021). Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. Transactions on Network and Service Management.https://doi.org/10.1109/TNSM.2021.3076503 
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Schneider, S. B., Karl, H., Khalili, R., &; Hecker, A. (2021). DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning.
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Bender, A. (2021). A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions. Machines, 9(10), Article 210.https://doi.org/10.3390/machines9100210 
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Bender, A., &; Sextro, W. (2021). Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties. In P. Do, S. King, &;https://doi.org/10.36001/phme.2021.v6i1.2843 __Olga Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021 (Vol. 6, Issue 1).https://doi.org/10.36001/phme.2021.v6i1.2843  
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Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H., &; Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers &; Operations Research, 136, 105489.https://doi.org/10.1016/j.cor.2021.105489 
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Beverungen, D., Kundisch, D., &; Wünderlich, N. (2021). Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers. Journal of Service Management, 32(4), 507–532.https://doi.org/10.1108/JOSM-03-2020-0066 
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Castenow, J., Feldkord, B., Knollmann, T., Malatyali, M., &; Meyer auf der Heide, F. (2020). The Online Multi-Commodity Facility Location Problem. In Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures.https://doi.org/10.1145/3350755.3400281 
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arXiv: 2005.08391

Camps-Mur, D.,  Canellas, F., Machwe, A., Paracuellos, J., Choumas, K., Giatsios, D.,  Razzaghi Kouchaksaraei, H. (n.d.). 5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services. In the 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020). Ghent, Belgium.
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Uhe, B., Kuball, C.-M., Merklein, M., &; Meschut, G. (2020). Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints. Production Engineering, 14, 417–423.https://doi.org/10.1007/s11740-020-00973-w 
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Bossek, J., Kerschke, P., &; Trautmann, H. (2020). A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Applied Soft Computing, 88, 105901.https://doi.org/10.1016/j.asoc.2019.105901 
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Bossek, J., Grimme, C., &; Trautmann, H. (2020). Dynamic Bi-Objective Routing of Multiple Vehicles. Proceedings of the Genetic and Evolutionary Computation Conference, 166–174.https://doi.org/10.1145/3377930.3390146 
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Bossek, J., Kerschke, P., &; Trautmann, H. (2020). A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms. Applied Soft Computing, 88(C).https://doi.org/10.1016/j.asoc.2019.105901 
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