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Optimal Inverse Design Based on Memetic Algorithms - Part 1 : Theory and Implementation

Capek, Miloslav LU ; Jelinek, Lukas ; Kadlec, Petr and Gustafsson, Mats LU orcid (2023) In IEEE Transactions on Antennas and Propagation 71(11). p.8806-8816
Abstract

A memetic framework for optimal inverse design is proposed by combining a local gradient-based procedure and a robust global scheme. The procedure is based on method-of-moments matrices and does not demand full inversion of a system matrix. Fundamental bounds are evaluated for all optimized metrics in the same manner, providing natural stopping criteria and quality measures for realized devices. Compared to density-based topology optimization, the proposed routine does not require filtering or thresholding. Compared to commonly used heuristics, the technique is significantly faster, still preserving a high level of versatility and robustness. This is a two-part paper in which the first part is devoted to the theoretical background and... (More)

A memetic framework for optimal inverse design is proposed by combining a local gradient-based procedure and a robust global scheme. The procedure is based on method-of-moments matrices and does not demand full inversion of a system matrix. Fundamental bounds are evaluated for all optimized metrics in the same manner, providing natural stopping criteria and quality measures for realized devices. Compared to density-based topology optimization, the proposed routine does not require filtering or thresholding. Compared to commonly used heuristics, the technique is significantly faster, still preserving a high level of versatility and robustness. This is a two-part paper in which the first part is devoted to the theoretical background and properties, and the second part applies the method to examples of varying complexity.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Antennas, inverse design, numerical methods, optimization methods, shape sensitivity analysis, structural topology design
in
IEEE Transactions on Antennas and Propagation
volume
71
issue
11
pages
8806 - 8816
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85169700469
ISSN
0018-926X
DOI
10.1109/TAP.2023.3308587
language
English
LU publication?
yes
id
74173a39-6c8f-425d-825f-037b6d59966e
date added to LUP
2023-11-06 14:58:12
date last changed
2024-01-09 15:45:13
@article{74173a39-6c8f-425d-825f-037b6d59966e,
  abstract     = {{<p>A memetic framework for optimal inverse design is proposed by combining a local gradient-based procedure and a robust global scheme. The procedure is based on method-of-moments matrices and does not demand full inversion of a system matrix. Fundamental bounds are evaluated for all optimized metrics in the same manner, providing natural stopping criteria and quality measures for realized devices. Compared to density-based topology optimization, the proposed routine does not require filtering or thresholding. Compared to commonly used heuristics, the technique is significantly faster, still preserving a high level of versatility and robustness. This is a two-part paper in which the first part is devoted to the theoretical background and properties, and the second part applies the method to examples of varying complexity.</p>}},
  author       = {{Capek, Miloslav and Jelinek, Lukas and Kadlec, Petr and Gustafsson, Mats}},
  issn         = {{0018-926X}},
  keywords     = {{Antennas; inverse design; numerical methods; optimization methods; shape sensitivity analysis; structural topology design}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{8806--8816}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Antennas and Propagation}},
  title        = {{Optimal Inverse Design Based on Memetic Algorithms - Part 1 : Theory and Implementation}},
  url          = {{http://dx.doi.org/10.1109/TAP.2023.3308587}},
  doi          = {{10.1109/TAP.2023.3308587}},
  volume       = {{71}},
  year         = {{2023}},
}