Email this article 
Comparison of a Genetic Algorithm and Evolutionary Strategies in Optimization of Strip-Structure Modal Filters
- Authors: Belousov A.O.1, Gordeeva V.O.1
-
Affiliations:
- Tomsk State University of Control Systems and Radioelectronics
- Issue: Vol 68, No 11 (2023)
- Pages: 1079-1089
- Section: ТЕОРИЯ И МЕТОДЫ ОБРАБОТКИ СИГНАЛОВ
- URL: https://kazanmedjournal.ru/0033-8494/article/view/650742
- DOI: https://doi.org/10.31857/S0033849423110037
- EDN: https://elibrary.ru/AUYLSC
- ID: 650742
Cite item
Open Access
Access granted
Subscription Access
Abstract
The features arising from the optimization of strip modal filters (MFs) using a genetic algorithm (GA) and evolutionary strategies (ESs) are considered. Sequential optimization of microstrip MFs and MFs with broad-side coupling was performed according to the criterion of minimizing the maximum amplitude of the output voltage. The results of such optimization with different numbers of calculations are presented, including the values of the optimized parameters, the objective function, the time spent on the calculation, stopping criteria (when optimized by ESs) and the voltage waveforms at the output of the studied MFs. A detailed analysis of the results of the two algorithms is presented. The advantages and disadvantages, as well as differences in the operation of each algorithm, are determined using the example of optimization of two MFs.
About the authors
A. O. Belousov
Tomsk State University of Control Systems and Radioelectronics
Email: ant1lafleur@gmail.com
634050, Tomsk, Russia
V. O. Gordeeva
Tomsk State University of Control Systems and Radioelectronics
Author for correspondence.
Email: ant1lafleur@gmail.com
634050, Tomsk, Russia
References
- Фоминич Э.Н., Владимиров Д.Р. // Военный инженер. 2016. № 2. С. 10.
- Электромагнитный терроризм на рубеже тысячелетий / Под ред. Т.Р. Газизова. Томск: Том. гос. ун-т, 2002.
- Mora N., Vega F., Lugrin G. et al. // System and Assessment Notes. 2014. № 41. P. 1.
- Gazizov A.T., Zabolotsky A.M., Gazizov T.R. // IEEE Trans. 2016. V. EMC-58. № 4. P. 1136. https://doi.org/10.1109/TEMC.2016.2548783
- Аоки М. Введение в методы оптимизации. М.: Наука, 1977.
- Gazizov R.R., Kuharenko M.N., Gazizov T.R. // Proc. Conf. Dynamics of Systems, Mechanisms and Machines. Omsk. 14–16 Nov. 2017. N.Y.: IEEE, 2017. P. 1. https://doi.org/10.1109/Dynamics.2017.8239452
- Gazizov R.R., Gazizov R.R., Zabolotsky A.M. // Proc. Int. Sib. Conf. on Control and Communication. Moscow. 14−16 March 2018. N.Y.: IEEE, 2018. P. 1. https://doi.org/10.1109/MWENT.2018.8337215
- Belousov A.O., Gazizov T.R. // Complexity. 2018. V. 2018. P. 1. https://doi.org/10.1155/2018/5676504
- Belousov A.O., Chernikova E.B., Samoylichenko M.A. et al. // Symmetry. 2020. V. 12. № 1117. P. 1. https://doi.org/10.3390/sym12071117
- Freisleben B., Merz P. // Proc. of IEEE Int. Conf. on Evolutionary Computation. 20–22 May. N.Y.: IEEE, 1996. P. 616. https://doi.org/10.1109/ICEC.1996.542671
- Mittra R., Chakravarty S., Yeo J. // IEEE Antennas and Propagation Society Int. Symp. 16–21 June. 2002. N.Y.: IEEE, 2002. P. 306. https://doi.org/10.1109/APS.2002.1016309
- Yegin K., Martin A.Q. // IEEE Trans. 2003. V. AP-51. № 2. P. 220. https://doi.org/10.1109/TAP.2003.809056
- Бураков М.В. Генетический алгоритм: теория и практика: уч. пособие. СПб.: ГУАП, 2008.
- Holland J.H. Adaptation in Natural and Artificial Systems. L.: MIT Press, 1975.
- Семеникин Е.С., Жукова М.Н., Жуков В.Г. и др. Эволюционные методы моделирования и оптимизации сложных систем. Конспект лекций. Красноярск: Сиб. федер. ун-т, 2007.
- Hansen N., Ostermeier A. // Evolutionary Computation. 2001. V. 9. № 2. P. 159.
- Kuksenko S.P. // IOP: Conf. Ser.: Materials Science and Engineering, 2019. V. 560. Article No. 01210.
- Hansen N. Python: module barecmaes2. http://www.cmap. polytechnique.fr/~nikolaus.hansen/ barecmaes2.html.
- Белоусов А.О., Гордеева В.О. // Докл. XVII междунар. науч.-практич. конф. “Электронные средства и системы управления”. Томск. 19–21 ноября 2021. С. 13.
Supplementary files
