Thesis Details
Paralelní genetický algoritmus
The thesis describes design and implementation of various evolutionary algorithms, which were enhanced to use the advantages of parallelism on the multiprocessor systems along with ability to run the computation on different machines in a computer network. The purpose of these algorithms is to find the global extreme of function of $n$ variables. In the thesis, there are demonstrated various optimization problems, and their effective solution with the help of evolutionary algorithms. There are also described interface libraries MPI(Message Passing Interface) and OpenMP, in the extent needed to understand the problematic of parallel evolutionary algorithms.
evolutionary algorithm, genetic algorithm, Message Passing Interface, MPI, OpenMP, global extreme, minimum, maximum, cost function, fitness function, parallelisation, parallel, neural network, inverse fractal problem, coeficients, fourier, queue, standard genetic algorithm, SGA, differential evolution, DE, self-organizing migrating algorithm, SOMA, stochastic hill climbing, SHC
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), člen
Lukáš Roman, Ing., Ph.D. (DIFS FIT BUT), člen
Ráček Jaroslav, RNDr., Ph.D. (FI MUNI), člen
Vojnar Tomáš, prof. Ing., Ph.D. (DITS FIT BUT), člen
Zbořil František, doc. Ing., Ph.D. (DITS FIT BUT), člen
@bachelorsthesis{FITBT4345,
author = "Jan Trupl",
type = "Bachelor's thesis",
title = "Paraleln\'{i} genetick\'{y} algoritmus",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2008,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/4345/"
}