Gebken, B. (2024). A note on the convergence of deterministic gradient sampling in nonsmooth optimization. Computational Optimization and Applications.https://doi.org/10.1007/s10589-024-00552-0 
LibreCat: /record/51208
DOI: 10.1007/s10589-024-00552-0

Bick, C., &; von der Gracht, S. (2024). Heteroclinic dynamics in network dynamical systems with higher-order interactions. Journal of Complex Networks, 12(2).https://doi.org/10.1093/comnet/cnae009 
LibreCat: /record/52726
DOI: 10.1093/comnet/cnae009
arXiv: 2309.02006

Prager, R. P., Dietrich, K., Schneider, L., Schäpermeier, L., Bischl, B., Kerschke, P., Trautmann, H., &; Mersmann, O. (2023). Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features. Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 129–139.https://doi.org/10.1145/3594805.3607136 
LibreCat: /record/47522
DOI: 10.1145/3594805.3607136

Bossek, J., Neumann, A., &; Neumann, F. (2023). On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. Proceedings of the Genetic and Evolutionary Computation Conference, 248–256.https://doi.org/10.1145/3583131.3590384 
LibreCat: /record/48869
DOI: 10.1145/3583131.3590384

Tao, Y., &; Winkler, M. (2023). Global smooth solutions in a three-dimensional cross-diffusive SIS epidemic model with saturated taxis at large densities. Evolution Equations and Control Theory, 12(6), 1676–1687.https://doi.org/10.3934/eect.2023031 
LibreCat: /record/53317
DOI: 10.3934/eect.2023031

Caillau, J.-B., Djema, W., Gouzé, J.-L., Maslovskaya, S., &; Pomet, J.-B. (2022). Turnpike Property in Optimal Microbial Metabolite Production. Journal of Optimization Theory and Applications.https://doi.org/10.1007/s10957-022-02023-0 
LibreCat: /record/30861
DOI: 10.1007/s10957-022-02023-0

Bonnard, B., Rouot, J., &; Wembe Moafo, B. E. (2022). Accessibility properties of abnormal geodesics in optimal control illustrated by two case studies. Mathematical Control and Related Fields, 0(0), 0–0.https://doi.org/10.3934/mcrf.2022052 
LibreCat: /record/35206
DOI: 10.3934/mcrf.2022052

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 
LibreCat: /record/31066
DOI: https://doi.org/10.1016/j.ifacol.2022.07.282

Philipo, G. H., Kakande, J. N., &; Krauter, S. (2022). Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. Energies, 15(14), Article 5215.https://doi.org/10.3390/en15145215 
LibreCat: /record/32403
DOI: 10.3390/en15145215

Philipo, G. H., Kakande, J. N., &; Krauter, S. (2022). Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. Energies, 15(14), Article 5215.https://doi.org/10.3390/en15145215 
LibreCat: /record/47961
DOI: 10.3390/en15145215

Hesse, M., Hunstig, M., Timmermann, J., &; Trächtler, A. (2022). Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design. Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM), 383–394.
LibreCat: /record/29803

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 
LibreCat: /record/48882
DOI: 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 
LibreCat: /record/48896
DOI: 10.1145/3520304.3528998

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 
LibreCat: /record/21004
DOI: 10.1109/tpami.2021.3051276

Schemmel, R., Krieger, V., Hemsel, T., &; Sextro, W. (2021). Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization. Microelectronics Reliability, 119, 114077.https://doi.org/10.1016/j.microrel.2021.114077 
LibreCat: /record/21436
DOI: https://doi.org/10.1016/j.microrel.2021.114077

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

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

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

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

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 
LibreCat: /record/48841
DOI: 10.1007/978-3-030-12598-1_41

Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., &; Trautmann, H. (2019). Evolving Diverse TSP Instances by Means of Novel and Creative Mutation Operators. Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 58–71.https://doi.org/10.1145/3299904.3340307 
LibreCat: /record/48842
DOI: 10.1145/3299904.3340307

Bossek, J., Neumann, F., Peng, P., &; Sudholt, D. (2019). Runtime Analysis of Randomized Search Heuristics for Dynamic Graph Coloring. Proceedings of the Genetic and Evolutionary Computation Conference, 1443–1451.https://doi.org/10.1145/3321707.3321792 
LibreCat: /record/48843
DOI: 10.1145/3321707.3321792

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 
LibreCat: /record/48840
DOI: 10.1145/3321707.3321818

Rauchecker, G., &; Schryen, G. (2018). Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief. In Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management. Rochester, NY, USA.
LibreCat: /record/5675

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 
LibreCat: /record/9999
DOI: 10.4071/2380-4505-2018.1.000572

Meyer, T. (2018). Optimization-based reliability control of mechatronic systems. Shaker.
LibreCat: /record/9994

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 
LibreCat: /record/48839
DOI: 10.1145/3205455.3205548

Bossek, J. (2018). Performance Assessment of Multi-Objective Evolutionary Algorithms with the R Package ecr. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1350–1356.https://doi.org/10.1145/3205651.3208312 
LibreCat: /record/48867
DOI: 10.1145/3205651.3208312

Kerschke, P., Bossek, J., &; Trautmann, H. (2018). Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1737–1744.https://doi.org/10.1145/3205651.3208233 
LibreCat: /record/48885
DOI: 10.1145/3205651.3208233

Mahnken, R. (2017). “A variational formulation for fuzzy analysis in continuum mechanics.” Mathematics and Mechanics of Complex Systems, 5(3–4).
LibreCat: /record/9862

Kaul, T., Meyer, T., &; Sextro, W. (2017). Formulation of reliability-related objective functions for design of intelligent mechatronic systems. SAGE Journals, Vol. 231(4), 390–399.https://doi.org/10.1177/1748006X17709376 
LibreCat: /record/9976
DOI: 10.1177/1748006X17709376

Ho, N., Kaufmann, P., &; Platzner, M. (2017). Evolvable caches: Optimization of reconfigurable cache mappings for a LEON3/Linux-based multi-core processor. In 2017 International Conference on Field Programmable Technology (ICFPT) (pp. 215–218).https://doi.org/10.1109/FPT.2017.8280144 
LibreCat: /record/10676
DOI: 10.1109/FPT.2017.8280144

Bossek, J. (2017). Ecr 2.0: A Modular Framework for Evolutionary Computation in R. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1187–1193.https://doi.org/10.1145/3067695.3082470 
LibreCat: /record/48863
DOI: 10.1145/3067695.3082470

Bossek, J., &; Grimme, C. (2017). A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning Tree Problem. 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1–8.https://doi.org/10.1109/SSCI.2017.8285183 
LibreCat: /record/48857
DOI: 10.1109/SSCI.2017.8285183

Meyer , T., Unger, A., Althoff, S., Sextro, W., Brökelmann, M., Hunstig, M., &; Guth, K. (2016). Reliable Manufacturing of Heavy Copper Wire Bonds Using Online Parameter Adaptation. In IEEE 66th Electronic Components and Technology Conference (pp. 622–628).https://doi.org/10.1109/ECTC.2016.215 
LibreCat: /record/9966
DOI: 10.1109/ECTC.2016.215

Bossek, J., &; Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037, 3–12.https://doi.org/10.1007/978-3-319-49130-1_1 
LibreCat: /record/48874
DOI: 10.1007/978-3-319-49130-1_1

Ho, N., Ahmed, A. F., Kaufmann, P., &; Platzner, M. (2015). Microarchitectural optimization by means of reconfigurable and evolvable cache mappings. In Proc. NASA/ESA Conf. Adaptive Hardware and Systems (AHS) (pp. 1–7).https://doi.org/10.1109/AHS.2015.7231178 
LibreCat: /record/10673
DOI: 10.1109/AHS.2015.7231178

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.”
LibreCat: /record/29973

Bossek, J., Bischl, B., Wagner, T., &; Rudolph, G. (2015). Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement. Proceedings of the Genetic and Evolutionary Computation Conference, 1319–1326.https://doi.org/10.1145/2739480.2754673 
LibreCat: /record/48838
DOI: 10.1145/2739480.2754673

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 
LibreCat: /record/48887
DOI: 10.1145/2739480.2754705