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Genetické algoritmy – implementace paralelního zpracování / Genetic Algorithms - Implementation of Multiprocessing

Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration originates in evolutionary principles in nature. Parallelization of genetic algorithms provides not only faster processing but also new and better solutions. Parallel genetic algorithms are also closer to real nature than their sequential counterparts. This paper describes the most used models of parallelization of genetic algorithms. Moreover, it provides the design and implementation in programming language Python. Finally, the implementation is verified in several test cases.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:377098
Date January 2018
CreatorsTuleja, Martin
ContributorsIlgner, Petr, Oujezský, Václav
PublisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Source SetsCzech ETDs
LanguageSlovak
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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