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4 Publications


2023 | Conference Paper | LibreCat-ID: 47522
Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features
R.P. Prager, K. Dietrich, L. Schneider, L. Schäpermeier, B. Bischl, P. Kerschke, H. Trautmann, O. Mersmann, in: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Association for Computing Machinery, New York, NY, USA, 2023, pp. 129–139.
LibreCat | DOI
 

2022 | Conference Paper | LibreCat-ID: 48882
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 | DOI
 

2021 | Journal Article | LibreCat-ID: 46318
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.
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2020 | Conference Paper | LibreCat-ID: 48849
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 | DOI
 

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