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Evolutionary Design of Boolean Functions for Cryptography
Dvořák, Jan ; Vašíček, Zdeněk (referee) ; Husa, Jakub (advisor)
The goal of this bachelor's thesis is to compare various selection methods used in cartesian genetic programming applied to a problem of various types of cryptographically significant boolean functions. I focused on these selection methods: evolutionary strategies (1+lambda) and (1,lambda), tournament selection and roulette selection. The chosen problem was solved by an implementation of CGP with the above-mentioned selection methods and by a statistical evaluation of data acquired from conducted experiments. Evaluation of mentioned data has shown that the best results in case of bent functions were achieved while using (1+lambda) evolutionary strategy. The roulette selection performed the best in case of balanced functions with high nonlinearity.
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Advanced Evolutionary Optimisation of TSP-Based Problems
Hladyuk, Vadym ; Vašíček, Zdeněk (referee) ; Bidlo, Michal (advisor)
This paper solves the traveling salesman problem using an evolutionary algorithm, specifically a genetic algorithm. It is a hybrid of the genetic algorithm, using a local search algorithm and other enhancements that further improve the results obtained. The traveling salesman problem will be solved from 20 cities to 25,000 cities. In the experiments chapter, I have determined the best settings for all the parameters in the program and properly tested their appropriateness. In the next part of the experiments chapter, I found out the performance of the full version of the genetic algorithm and its variants. In the last section, I compared the evolution of fitness values of different variants of genetic algorithms and different variants of crossover operators, I also compared the time consumption. I suggested further possible improvements either to the local search algorithm or to another approach to solve the TSP.
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Evolutionary Design of Boolean Functions for Cryptography
Dvořák, Jan ; Vašíček, Zdeněk (referee) ; Husa, Jakub (advisor)
The goal of this bachelor's thesis is to compare various selection methods used in cartesian genetic programming applied to a problem of various types of cryptographically significant boolean functions. I focused on these selection methods: evolutionary strategies (1+lambda) and (1,lambda), tournament selection and roulette selection. The chosen problem was solved by an implementation of CGP with the above-mentioned selection methods and by a statistical evaluation of data acquired from conducted experiments. Evaluation of mentioned data has shown that the best results in case of bent functions were achieved while using (1+lambda) evolutionary strategy. The roulette selection performed the best in case of balanced functions with high nonlinearity.
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