Detail publikace

Parallel Processing of Genetic Algorithms in Python Language

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"
}