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Antenna Switch Optimizations Using Genetic Algorithms Accelerated With the Multilevel Fast Multipole Algorithm
Date
2015-07-24
Author
Onol, Can
Karaosmanoglu, Bariscan
Ergül, Özgür Salih
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We present antenna switch optimizations using an efficient mechanism based on genetic algorithms and the multi-level fast multipole algorithm (MLFMA). Genetic algorithms are used to determine switch states for desired radiation and input characteristics, while cost-function evaluations are performed efficiently via an MLFMA implementation with dynamic error control. MLFMA is integrated into the genetic algorithm by extracting common computations to be performed once per optimization. Iterative convergence rates are further accelerated by using earlier solutions as initial-guess vectors. The efficiency of the developed mechanism is demonstrated on antennas with relatively large numbers of switches.
Subject Keywords
Optimization
,
Switches
,
Genetic algorithms
,
Dipole antennas
,
MLFMA
,
Directive antennas
URI
https://hdl.handle.net/11511/46989
DOI
https://doi.org/10.1109/aps.2015.7305058
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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BibTeX
C. Onol, B. Karaosmanoglu, and Ö. S. Ergül, “Antenna Switch Optimizations Using Genetic Algorithms Accelerated With the Multilevel Fast Multipole Algorithm,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46989.
