Advances in Radio Science
Advances in Radio Science
ARS
Articles | Volume 21
Articles | Volume 21
https://doi.org/10.5194/ars-21-123-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ars-21-123-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21
20 Aug 2024
 | 20 Aug 2024

Iterative Placement of Decoupling Capacitors using Optimization Algorithms and Machine Learning

Zouhair Nezhi, Nima Ghafarian Shoaee, and Marcus Stiemer

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Latest update: 13 Dec 2024
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Short summary
An optimum placement and dimensioning of decaps on a printed circuit board is determined by a Genetic Algorithm (GA). The use of an artificial neural network as surrogate model to compute fitness values for the GA significantly reduces computation time. With the optimization framework at hand, the risk of a redesign that would take several weeks can be significantly reduced by a computation that just needs a few minutes.
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