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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Citation Formats

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.