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4 Publications
2023 | Conference Paper | LibreCat-ID: 47522
Prager RP, Dietrich K, Schneider L, et al. Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features. In: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. FOGA ’23. Association for Computing Machinery; 2023:129–139. doi:10.1145/3594805.3607136
LibreCat
| DOI
2022 | Conference Paper | LibreCat-ID: 48882
Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tusar T, eds. Parallel Problem Solving from Nature (PPSN XVII). Lecture Notes in Computer Science. Springer International Publishing; 2022:192–206. doi:10.1007/978-3-031-14714-2_14
LibreCat
| DOI
2021 | Journal Article | LibreCat-ID: 46318
Grimme C, Kerschke P, Aspar P, et al. Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research. 2021;136:105489. doi:https://doi.org/10.1016/j.cor.2021.105489
LibreCat
| DOI
2020 | Conference Paper | LibreCat-ID: 48849
Bossek J, Doerr C, Kerschke P, Neumann A, Neumann F. Evolving Sampling Strategies for One-Shot Optimization Tasks. In: Parallel Problem Solving from Nature (PPSN XVI). Springer-Verlag; 2020:111–124. doi:10.1007/978-3-030-58112-1_8
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