Original title: Paralelní optimalizační metody
Translated title: Parallel optimization methods
Authors: Marcina, Tomáš ; Kozovský, Matúš (referee) ; Kozubík, Michal (advisor)
Document type: Bachelor's theses
Year: 2023
Language: slo
Publisher: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Abstract: [slo] [eng]
Práca je zameraná na porovnanie rôznych algoritmov určených pre optimalizáciu viacrozmerných funkcií. Konkrétne sa zaoberá populačnými metódami optimalizácií, ktoré sú vo všeobecnosti vhodné pre paralelizovanie výpočtu optimálnej hodnoty funkcie. Funkcie sú implementované v programe Matlab a na platforme NVIDIA CUDA. Porovnáva niekoľko rôznych algoritmov na to vhodných. Na záver sú zhrnuté výhody a nevýhody jednotlivých algoritmov. The work is concerned on the comparison of different algorithms designed for the optimization of multidimensional functions. Specifically, it deals with population optimization methods, which are generally suitable for parallelizing the calculation of the optimal function value. The functions are implemented in program Matlab and on the NVIDIA CUDA platform. It compares several different algorithms suitable for this. At the end, the advantages and disadvantages of individual algorithms are summarized.
Keywords: artificial bee colony algorithm; CUDA.; differential Evolution; firefly algorithm; grey wolf optimalization; Optimalization; parallel optimizations; particle swarm optimization

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/210972

Permalink: http://www.nusl.cz/ntk/nusl-529253


The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Academic theses (ETDs) > Bachelor's theses