|
|
Optimisation of TSP-Based Tasks Using Collective Computational Intelligence
Franěk, Jaromír ; Jaroš, Jiří (referee) ; Bidlo, Michal (advisor)
The aim of this work is to compare collective computational intelligence algorithms for the optimization of large-scale instances of traveling salesman problem consisting of in several of thousands of cities. This work will be focused on optimization based on swarm behavior and optimization based on bee swarm behavior. I have compared individual algorithms from these two approaches with different parameters within a set of experiments. Based on these results, I proposed an improvement to the algorithms for solving the given problem. Then I proposed an improvement to the algorithms using diversity support methods, or local search for discrete versions of these algorithms. Finally, I compared results of proposed algorithms within a final set of experiments.
|
|
|
Nature-Inspired Optimisation Algorithms
Krampla, Vojtěch ; Dvořák, Jiří (referee) ; Šeda, Miloš (advisor)
This work focuses on the description of four nature-inspired optimization algorithms. The ant colony algorithm, the grey wolf algorithm, the bee swarm algorithm, and the genetic algorithm are described. As part of this work, the genetic algorithm was implemented for an optimization task, specifically for solving the knapsack problem. The work includes an experiment with this algorithm and an evaluation of the obtained results.
|
|
|
Evolutionary Circuit Design by Means of Genetic Programming
Synák, Maroš ; Hurta, Martin (referee) ; Bidlo, Michal (advisor)
Tato práce zkoumá aplikaci genetického programování (GP) pro návrh elektronických obvodů, zaměřuje se na sinusové a obdélníkové oscilátory a diskriminátory tónů, s použitím Pythonu a PySpice. Cílem je znovu vytvořit aspekty základní práce Johna Kozy v tomto oboru. Hlavním cílem je posoudit, zda může GP generovat pokročilé elektronické návrhy efektivněji než tradiční metody, přizpůsobujíc přitom Kozy genetické operace - výběr, křížení, mutaci - moderním výzvám v návrhu obvodů. Metodologie zahrnuje vývoj modelů GP pro simulaci evolučního návrhu obvodů, hodnocených prostřednictvím kontrolovaných experimentů. Tyto experimenty testují schopnost modelů vyvíjet se od základních po složité konfigurace, které splňují specifické elektronické funkce. Tato studie nejenže přezkoumává, ale také upravuje Kozy metody, zahrnuje strategie více závislé na počátečním nastavení embrya, aby řídily evoluční proces v generování cílených návrhů. Kromě toho studie zkoumá nedávné metodologie využívané v podobných aplikacích, aby zvýšila adaptabilitu a efektivitu GP. Výsledky ukazují, že zatímco GP může účinně podporovat a zlepšovat návrh elektronických obvodů pro sinusové oscilátory a diskriminátory tónů, jeho aplikace na generování obdélníkových oscilátorů narazí na omezení a vážné problémy. To zdůrazňuje oblasti pro potenciální zlepšení v genetické diverzitě a zdokonalení algoritmů. Celkově tato práce zdůrazňuje potenciál genetického programování v revoluci návrhu elektronických obvodů, což naznačuje další průzkum a zdokonalení Kozy metodologií, které by mohly rozšířit aplikovatelnost GP v oboru. Tato práce představuje jak pokračování, tak evoluci jeho průkopnických úsilí, čímž otevírá cestu pro budoucí inovace v elektronickém inženýrství.
|
|
|
Ant colony
Hart, Pavel ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
First part of the thesis is about literature research of optimization algorithms. Three of the algorithms were implemented and tested, concretely the ant colony algorithm, tabu search and simulated annealing. All three algorithms were implemented to solve the traveling salesman problem. In second part of the thesis the algorithms were tested and compared. In last part the influence of the ant colony parameters was evaluated.
|
|
|
Overview of Actual Approaches to Optimization
Hudecová, Patrícia ; Šůstek, Martin (referee) ; Zbořil, František (advisor)
This work aimed to study some of the optimization algorithms inspired by nature and to test their success in finding the extreme of a function on various functions. Four algorithms were selected, namely the bat algorithm, the firefly algorithm, the flower pollination algorithm, and the black hole algorithm. The Griewank function, the Rastringin function, and the Rosenbrock function were chosen as test functions for finding the extreme of the function. The work contains a description of individual algorithms, a description of test functions and a description of the experiments, and an evaluation of the success of the algorithms.
|
|
|
Evolutionary algorithms
Haupt, Daniel ; Polách, Petr (referee) ; Honzík, Petr (advisor)
The first part of this work deals with the optimization and evolutionary algorithms which are used as a tool to solve complex optimization problems. The discussed algorithms are Differential Evolution, Genetic Algorithm, Simulated Annealing and deterministic non-evolutionary algorithm Taboo Search.. Consequently the discussion is held on the issue of testing the optimization algorithms through the use of the test function gallery and comparison solution all algorithms on Travelling salesman problem. In the second part of this work all above mentioned optimization algorithms are tested on 11 test functions and on three models of placement cities in Travelling salesman problem. Firstly, the experiments are carried out with unlimited number of accesses to the fitness function and secondly with limited number of accesses to the fitness function. All the data are processed statistically and graphically.
|
|
|
Optimization Algorithms Inspired by Nature
Babjarčiková, Lenka ; Zbořil, František (referee) ; Zbořil, František (advisor)
This thesis deals with four optimization algorithms inspired by nature. It describes ant colony optimization algorithm, marriage in honeybees optimization algorithm, grey wolf optimization algorithm and simulated annealing algorithm. The main part of this thesis is the application of these algorithms for solving three optimization problems. One of the problems is travelling salesman problem, which is solved by ant colony optimization, next problem is searching for extreme of function solved by grey wolf optimization and simulated annealing algorithms and the last is boolean satisfiability problem solved by marriage in honeybees optimization algorithm. Thesis contains experiments with these algorithms and reviews gained results.
|
|
| |
|
|
Video stabilization using global optimization algorithms
Bartoš, Patrik ; Říha, Kamil (referee) ; Kříž, Petr (advisor)
This bachelor thesis focuses on video stabilization using CRS (Controlled Random Search) and GA (Genetic Algorithm) optimization algorithms. It describes registration process, geometrical transformations, interpolation methods, similarity criteria and optimization algorithms. It also briefly describes structure of the program created in MATLAB. Finally it contains results of achieved stabilization.
|
|
|
Overview of Nature-Inspired Optimization Algorithms
Jendrálová, Martina ; Zbořil, František (referee) ; Zbořil, František (advisor)
The aim of this work was to investigate and compare the efficiency of four nature-inspired optimization algorithms in finding function extremes on various test functions. The algorithms included the cat swarm optimization algorithm, social-emotional optimization algorithm, dolphin echolocation algorithm, and harmony search algorithm. The chosen test functions for extreme searching were Rosenbrock function, Griewank function, and Rastrigin function. The work includes descriptions of individual experiments and evaluates the success of these algorithms in finding function extremes.
|
guest ::
