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ŠKORPIL, V. OUJEZSKÝ, V. TULEJA, M.
Originální název
Comparison of Models of Parallelized Genetic Algorithms
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
The aim of the paper is to describe the most widely used methods of parallelization of GA genetic algorithms and subsequently to use the outputs of the theoretical part for the design of implementation. Python was chosen as the implementation language, so the design is implemented with this language in mind. Selected problems of sequential GA are described in the theoretical part of the paper. Optimization problems and parallel models are described. 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. The practical part deals with the design and implementation of parallelized GA.
Klíčová slova
genetic algorithm; multiprocessing; model; optimization; parallelization; Python
Autoři
ŠKORPIL, V.; OUJEZSKÝ, V.; TULEJA, M.
Vydáno
30. 10. 2019
Nakladatel
IEEE
Místo
Dublin, Irsko
ISBN
978-1-7281-5763-4
Kniha
Proceedings of the 11th IEEE International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2019)
ISSN
2157-023X
Periodikum
International Congress on Ultra Modern Telecommunications and Control Systems and Workshops
Stát
neuvedeno
Strany od
1
Strany do
5
Strany počet
URL
https://ieeexplore.ieee.org/document/8970944
BibTex
@inproceedings{BUT159752, author="Vladislav {Škorpil} and Václav {Oujezský} and Martin {Tuleja}", title="Comparison of Models of Parallelized Genetic Algorithms", booktitle="Proceedings of the 11th IEEE International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2019)", year="2019", journal="International Congress on Ultra Modern Telecommunications and Control Systems and Workshops", pages="1--5", publisher="IEEE", address="Dublin, Irsko", doi="10.1109/ICUMT48472.2019.8970944", isbn="978-1-7281-5763-4", issn="2157-023X", url="https://ieeexplore.ieee.org/document/8970944" }