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Optimalizace metaheuristikami v Pythonu pomocí knihovny DEAP / Optimization by means of metaheuristics in Python using the DEAP library

{This thesis deals with optimization by means of metaheuristics, which are used for complicated engineering problems that cannot be solved by classical methods of mathematical programming. At the beginning, choosed metaheuristics are described: simulated annealing, particle swarm optimization and genetic algorithm; and then they are compared with use of test functions. These algorithms are implemented in Python programming language with use of package called DEAP, which is also described in this thesis. Algorithms are then applied for optimization of design parameters of the heat storage unit.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:401489
Date January 2019
CreatorsKesler, René
ContributorsCharvát, Pavel, Klimeš, Lubomír
PublisherVysoké učení technické v Brně. Fakulta strojního inženýrství
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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