Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
ŠKORPIL, V. OUJEZSKÝ, V. ČÍKA, P. TULEJA, M.
Originální název
Parallel Processing of Genetic Algorithms in Python Language
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Modern genetic algorithms are derived from natural laws and phenomenons and belong to evolutionary algorithms. Genetic algorithms are, by their very nature, suitable for parallel processing that leads to increased speed and to optimization. The paper deals with selected ways of parallelization of genetic algorithms with subsequent implementation. Parallelization brings an increase in algorithm speed and load distribution, which is compared to a serial model. Python language is used for demonstration. Four Python modules have been selected to provide parallel processing. They are the Global One - Population Master-Slave Model, the One-Population Fine-Grained Model, the Multi-Population Coarse-Grained Model, and the Hierarchical Model.
Klíčová slova
genetic algorithm; parallel processing; model; Python
Autoři
ŠKORPIL, V.; OUJEZSKÝ, V.; ČÍKA, P.; TULEJA, M.
Vydáno
17. 6. 2019
Nakladatel
IEEE
Místo
Rome, Italy
ISBN
978-4-88552-316-8
Kniha
2019 Progress in Electomagnetics Research Symposium (PIERS - Rome)
ISSN
1559-9450
Periodikum
Progress In Electromagnetics
Stát
Spojené státy americké
Strany od
3727
Strany do
3731
Strany počet
5
URL
https://ieeexplore.ieee.org/abstract/document/9017332
BibTex
@inproceedings{BUT159755, author="Vladislav {Škorpil} and Václav {Oujezský} and Petr {Číka} and Martin {Tuleja}", title="Parallel Processing of Genetic Algorithms in Python Language", booktitle="2019 Progress in Electomagnetics Research Symposium (PIERS - Rome)", year="2019", journal="Progress In Electromagnetics", pages="3727--3731", publisher="IEEE", address="Rome, Italy", doi="10.1109/PIERS-Spring46901.2019.9017332", isbn="978-4-88552-316-8", issn="1559-9450", url="https://ieeexplore.ieee.org/abstract/document/9017332" }