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4 Publications
2023 | Conference Paper | LibreCat-ID: 47522
Prager, Raphael Patrick, Konstantin Dietrich, Lennart Schneider, Lennart Schäpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, and Olaf Mersmann. “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, 129–139. FOGA ’23. New York, NY, USA: Association for Computing Machinery, 2023. https://doi.org/10.1145/3594805.3607136.
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2022 | Conference Paper | LibreCat-ID: 48882
Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_14.
LibreCat
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2021 | Journal Article | LibreCat-ID: 46318
Grimme, Christian, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, and Michael Emmerich. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” Computers & Operations Research 136 (2021): 105489. https://doi.org/10.1016/j.cor.2021.105489.
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2020 | Conference Paper | LibreCat-ID: 48849
Bossek, Jakob, Carola Doerr, Pascal Kerschke, Aneta Neumann, and Frank Neumann. “Evolving Sampling Strategies for One-Shot Optimization Tasks.” In Parallel Problem Solving from Nature (PPSN XVI), 111–124. Berlin, Heidelberg: Springer-Verlag, 2020. https://doi.org/10.1007/978-3-030-58112-1_8.
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