Automatic hyperparameter tuning of topology optimization algorithms using surrogate optimization
This paper presents a new approach that automates the tuning process in topology optimization of parameters that are traditionally defined by the user. The new method draws inspiration from hyperparameter optimization in machine learning. A new design problem is formulated where the topology optimiz...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Berlin Heidelberg
2024
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| Online Access: | https://hdl.handle.net/1721.1/156697 |