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 
LibreCat: /record/46318
DOI: https://doi.org/10.1016/j.cor.2021.105489

Bossek, J., Neumann, A., &; Neumann, F. (2021). Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference, 556–564.https://doi.org/10.1145/3449639.3459364 
LibreCat: /record/48853
DOI: 10.1145/3449639.3459364

Bossek, J., &; Neumann, F. (2021). Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 198–206.https://doi.org/10.1145/3449639.3459363 
LibreCat: /record/48860
DOI: 10.1145/3449639.3459363

Bossek, J., Neumann, F., Peng, P., &; Sudholt, D. (2021). Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. Algorithmica, 83(10), 3148–3179.https://doi.org/10.1007/s00453-021-00838-3 
LibreCat: /record/48854
DOI: 10.1007/s00453-021-00838-3

Schneider, S. B., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., Khalili, R., &; Hecker, A. (2020). Self-Driving Network and Service Coordination Using Deep Reinforcement Learning. In IEEE International Conference on Network and Service Management (CNSM). IEEE.
LibreCat: /record/19609

Kuball, C.-M., Uhe, B., Meschut, G., &; Merklein, M. (Eds.). (2020). Process design for the forming of semi-tubular self-piercing rivets made of high nitrogen steel (Vol. 50, pp. 280–285).https://doi.org/10.1016/j.promfg.2020.08.052 
LibreCat: /record/19976
DOI: 10.1016/j.promfg.2020.08.052

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 
LibreCat: /record/17370
DOI: 10.1145/3350755.3400281
arXiv: 2005.08391

Otroshi, M., Rossel, M., &; Meschut, G. (2020). Stress state dependent damage modeling of self-pierce riveting process simulation using GISSMO damage model. Journal of Advanced Joining Processes, 1.https://doi.org/10.1016/j.jajp.2020.100015 
LibreCat: /record/20143
DOI: 10.1016/j.jajp.2020.100015

Caruso, C., Adammek, C., Bonanati, S., &; Wiescholek, S. (2020). Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen. Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion, 3(1), 18–33.https://doi.org/10.4119/hlz-2540 
LibreCat: /record/35298
DOI: 10.4119/hlz-2540

Bonnard, B., Cots, O., &; Wembe Moafo, B. E. (2020). A Zermelo navigation problem with a vortex singularity. ESAIM: Control, Optimisation and Calculus of Variations, 27, Article .https://doi.org/10.1051/cocv/2020058 
LibreCat: /record/33866
DOI: 10.1051/cocv/2020058

Kuball, C.-M., Jung, R., Uhe, B., Meschut, G., &; Merklein, M. (Eds.). (2020). Influence of the process temperature on the forming behaviour and the friction during bulk forming of high nitrogen steel (No. 100023; Vol. 1).https://doi.org/10.1016/j.jajp.2020.100023 
LibreCat: /record/19974
DOI: 10.1016/j.jajp.2020.100023

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 
LibreCat: /record/19973
DOI: 10.1007/s11740-020-00973-w

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 
LibreCat: /record/46334
DOI: https://doi.org/10.1016/j.asoc.2019.105901

Bossek, J., Neumann, F., Peng, P., &; Sudholt, D. (2020). More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization. Proceedings of the Genetic and Evolutionary Computation Conference, 1277–1285.https://doi.org/10.1145/3377930.3390174 
LibreCat: /record/48847
DOI: 10.1145/3377930.3390174

Bossek, J., Doerr, C., Kerschke, P., Neumann, A., &; Neumann, F. (2020). Evolving Sampling Strategies for One-Shot Optimization Tasks. Parallel Problem Solving from Nature (PPSN XVI), 111–124.https://doi.org/10.1007/978-3-030-58112-1_8 
LibreCat: /record/48849
DOI: 10.1007/978-3-030-58112-1_8

Bossek, J., Casel, K., Kerschke, P., &; Neumann, F. (2020). The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics. Proceedings of the Genetic and Evolutionary Computation Conference, 1286–1294.https://doi.org/10.1145/3377930.3390243 
LibreCat: /record/48851
DOI: 10.1145/3377930.3390243

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 
LibreCat: /record/48845
DOI: 10.1145/3377930.3390146

Bossek, J., Doerr, C., &; Kerschke, P. (2020). Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB. Proceedings of the Genetic and Evolutionary Computation Conference, 778–786.https://doi.org/10.1145/3377930.3390155 
LibreCat: /record/48850
DOI: 10.1145/3377930.3390155

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 
LibreCat: /record/48848
DOI: 10.1016/j.asoc.2019.105901

Hippert, B., Uhde, A., &; Wengerek, S. T. (2019). Portfolio Benefits of Adding Corporate Credit Default Swap Indices: Evidence from North America and Europe. Review of Derivatives Research , 22(2), 203–259.https://doi.org/10.1007/s11147-018-9148-8 
LibreCat: /record/4562
DOI: https://doi.org/10.1007/s11147-018-9148-8