| 1. |
- Capek, Miloslav, et al.
(författare)
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Optimal Inverse Design Based on Memetic Algorithms - Part 1 : Theory and Implementation
- 2023
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Ingår i: IEEE Transactions on Antennas and Propagation. - 0018-926X. ; 71:11, s. 8806-8816
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Tidskriftsartikel (refereegranskat)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 properties, and the second part applies the method to examples of varying complexity.
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| 2. |
- Capek, Miloslav, et al.
(författare)
-
Optimal Inverse Design Based on Memetic Algorithms - Part II : Examples and Properties
- 2023
-
Ingår i: IEEE Transactions on Antennas and Propagation. - 0018-926X. ; 71:11, s. 8817-8829
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Tidskriftsartikel (refereegranskat)abstract
- Optimal inverse design, including topology optimization and evaluation of fundamental bounds on performance, which was introduced in Part 1, is applied to various antenna design problems. A memetic scheme for topology optimization combines local and global techniques to accelerate convergence and maintain robustness. Method-of-moments (MoMs) matrices are used to evaluate objective functions and allow determination of fundamental bounds on performance. By applying the Shermann-Morrison-Woodbury identity, the repetitively performed structural update is inversion-free yet full-wave. The technique can easily be combined with additional features often required in practice, e.g., only a part of the structure is controllable, or evaluation of an objective function is required in a subdomain only. The memetic framework supports multifrequency and multiport optimization and offers many other advantages, such as an actual shape being known at every moment of the optimization. The performance of the method is assessed, including its convergence and computational cost.
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