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 

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 

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 

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 

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 

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 

Bossek, J., Grimme, C., Meisel, S., Rudolph, G., &; Trautmann, H. (2019). Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm. In K. Deb, E. Goodman, C. A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, &; P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (pp. 516–528). Springer International Publishing.https://doi.org/10.1007/978-3-030-12598-1_41 

Bossek, J., Grimme, C., &; Neumann, F. (2019). On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 516–523.https://doi.org/10.1145/3321707.3321818 

Unger, A., Hunstig, M., Meyer, T., Brökelmann, M., &; Sextro, W. (2018). Intelligent Production of Wire Bonds using Multi-Objective Optimization – Insights, Opportunities and Challenges. In In Proceedings of IMAPS 2018 – 51st Symposium on Microelectronics, Pasadena, CA, 2018 (Vol. Vol. 2018, No. 1, pp. 000572-000577.).https://doi.org/10.4071/2380-4505-2018.1.000572 

Bossek, J., Grimme, C., Meisel, S., Rudolph, G., &; Trautmann, H. (2018). Local Search Effects in Bi-Objective Orienteering. Proceedings of the Genetic and Evolutionary Computation Conference, 585–592.https://doi.org/10.1145/3205455.3205548 

Stille, K. S. C., Böcker, J., Bettentrup, R., &; Kaiser, I. (2015). Hierarchisches Optimierungskonzept für die Laststeuerung von Haushaltsgeräten. ETG-Fachtagung “Von Smart Grids Zu Smart Markets.”

Meisel, S., Grimme, C., Bossek, J., Wölck, M., Rudolph, G., &; Trautmann, H. (2015). Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. Proceedings of the Genetic and Evolutionary Computation Conference , 425–432.https://doi.org/10.1145/2739480.2754705