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

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.
LibreCat: /record/48882
DOI: 10.1007/978-3-031-14714-2_14

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

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

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

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

Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms
J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 556–564.
LibreCat: /record/48853
DOI: 10.1145/3449639.3459364

Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem
J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 198–206.
LibreCat: /record/48860
DOI: 10.1145/3449639.3459363

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

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

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

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

More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization
J. Bossek, F. Neumann, P. Peng, D. Sudholt, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 1277–1285.
LibreCat: /record/48847
DOI: 10.1145/3377930.3390174

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

The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics
J. Bossek, K. Casel, P. Kerschke, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 1286–1294.
LibreCat: /record/48851
DOI: 10.1145/3377930.3390243

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.
LibreCat: /record/48845
DOI: 10.1145/3377930.3390146

Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB
J. Bossek, C. Doerr, P. Kerschke, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 778–786.
LibreCat: /record/48850
DOI: 10.1145/3377930.3390155

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

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

Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm
J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: K. Deb, E. Goodman, C.A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO), Springer International Publishing, Cham, 2019, pp. 516–528.
LibreCat: /record/48841
DOI: 10.1007/978-3-030-12598-1_41