•  
  •  
 

Abstract

In article discusses issues for solving optimization problems based on the use of genetic algorithms. To date, the genetic use algorithm for solving various problems. Which includes the shortest path search, approximation, data filtering and others. In particular, data is being examined regarding the use of a genetic algorithm to solve problems of optimizing the modes of electric power systems. Imagine an algorithm for developing the development of mathematical models, which includes developing the structure of the chromosome, creating a started population, creating a directing force for the population, etc. As well as the presentation, the selected structure should take into account all the features and limitations imposed on the desired solution, as well as the fact that the implementation of crossоver and mutation algorithms directly depends on its choice. To solve optimization problems, a block diagram of the genetic algorithm is given.

First Page

224

Last Page

229

DOI

https://doi.org/10.51346/tstu-01.19.3.-77-0030

References

1. Emilyanov V.V., Kureychik V.M. Teoriya I praktika evolyusionnogo modelirovaniya. - М: Fizmatlit, 2013. – s. 432.

2. Gladkov L.A., Kureychik V.V., Kureychik V.M. Geneticheskiye algoritmi: Uchebnoye posobiye. - 2-е izd. - М: Fiznatlit, 2006. - s. 320.

3. Darrel Whitley "A Genetic Algorithm Tutorial", 2016.-256 p.

4. Tsoy Yu.R., Spistin V.G. Geneticheskiy algoritm/Spisin V.G., Tsoy Yu.R. Predstavleniye znaniy v informatsionnix sistemax: uchebnoe posobie. -Tomsk: Izd-vo TPU, 2016. -146 s.

5. Gayibov T.Sh., Pulatov B.M., Qayumov J.A. Minimization of Losses in Distributed Power Networks by Genetic Algorithms.- International Journal of Advanced Research in Science, Engineering and Technology.-Vol. 6, Issue 2, February 2019.- pp. 8037-8039.

6. Deb K., Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons

7. AbdellahLaoufi , Collective Intelligence for Optimal Power Flow Solution Using Ant Colony Optimization, Leonardo Electronic Journal of Practices and Technologies, p.88-105,2008.

8. Gayibov T.Sh. Effektivniy algoritm optimizasii rejimov energosistem // Sbornik statey mejdunarodnoy nauchnoy konferensii «Innovasiya-2002». – Tashkent, 2002. – S. 90-91.

9. Rana S.B., Whitley L.D., Bit representations with a twist. – Proc. 7th International Conference of Genetic Algorithms, 1997.

10. Ruderich R., Fuel Cell Principles. Lecture notes. University of Applied Sciences, Ulm, Germany. 2003. 11. Sopov E.A. Probabilistic genetic programming design // Actual problems of informatics and intelligent techniques. - Tambov, 2004. - P. 98 – 99.

12. Larmine J., Dicks A. Fuel Cell Systems Explained, Second Edition. – John Wiley & Sons, Ltd, 2003.

13. Ruban A.I. Metodi optimizasii: Uchebnoe posobie. Izd. 2-ое. Krasnoyarsk NII IPU, 2001. 528 s.

14. Bartolomey P.I., Panikovskaya T.А. Optimizasiya rejomov energosistem: Uchebnoe posobie / Еkaterinburg: UGTU – UPI, 2008. - 164 s.

15. Makoklyuyev B.I. Analiz I planirovaniye elektropotrebleniya. – М.: Energoatomizdat, 2008. - 296 s. 16. Filippova T.A. i dr. Optimizasiya rejimov elektrostansiy i energosistem: Uchebnik; – Novosib. gos. texn. un-t. - Novosibirsk, 2007. - 356 s.

17. Suxanov О.А., Sharov Yu.V. Ierarxicheskiye modeli v analize i upravlenii rejimami elektroenergeticheskix system.– М.: Izdatelskiy dom MEI, 2007. – 312 s.

18. Likin A.V. Elektricheskie sistemi i seti: Ucheb. posobiye. – М.: Universitetskaya kniga; Logos, 2006. – 254 s.

19. Kochura А.V. Geneticheskiye algoritmi v MatLAB: metodicheskiye ukazaniya. – Kursk: Avtorskaya redaksiya, 2010. – 19 s

20. Whitley D.L. Genetic Algorithms and Evolutionary Computing. Van Nostrand's Scientific Encyclopedia 2002.

Included in

Engineering Commons

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.