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Application of Evolutionary Algorithms in Quantum Computing
Žufan, Petr ; Mrázek, Vojtěch (referee) ; Bidlo, Michal (advisor)
In this thesis, an evolutionary system for searching quantum operators in the form of unitary matrices is implemented. The aim is to propose several representations of candidate solutions and settings of the evolutionary algorithm. Two evolutionary algorithms were applied: the genetic algorithm and evolutionary strategy. Furthermore, a method of generating a unitary matrix is presented which is used for the first time for this task. This method is in some aspects better than the previous ones. Finally, a comparison of all used techniques is shown in experiments.
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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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Optimization of PID controller using evolutionary computing techniques
Kočí, Jakub ; Matoušek, Radomil (referee) ; Lang, Stanislav (advisor)
This bachelor thesis deals with using evolutionary computation for tuning up PID controller. In research part there are summarised information about regulation and another background information about quality of regulation and ITAE criterion. Practical part consist of implementing three evolutionary computation algorithms - differential evolution, evolution strategy and genetic algorithm. These and MATLAB's function ga() are compared on two systems mutually and to Ziegler-Nichols rule. Basic comparsion is followed by statistical evaluation on second system.
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The Impact of Candidate Solution Mappings on Evolutionary Algorithm Efficiency
Hrbáček, Jiří ; Korček, Pavol (referee) ; Křivánek, Jan (advisor)
The Concern of the present study is summarizing knowledges in the theory of mapping candidate solutions , analysis and application of evolutionary algorithms. The study provides summary of the evolutionary algorithms, classification and application. The target of the study is links gained knowledge from sectionS of ; evolutionary algorithms, mapping candidate solutions and creations of a system that will demonstrate and influence mapping the efficiency of the evolutionary algorithms succesfully.
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New Evolutionary Algorithms for Designing Cellular Automata
Ormandy, Adam ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
This thesis describes an evolutionary design of state-transition functions in cellular auto- mata built on conditionally matching rules. It presents a new algorithm ESP and its com- parison with already existing evolutionary techniques, specifically the evolutionary strategy and genetic algorithm. Chosen Case studies include self-replicating structures, moving ob- jects and development of patterns.
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Application of Evolutionary Algorithms in Quantum Computing
Žufan, Petr ; Mrázek, Vojtěch (referee) ; Bidlo, Michal (advisor)
In this thesis, an evolutionary system for searching quantum operators in the form of unitary matrices is implemented. The aim is to propose several representations of candidate solutions and settings of the evolutionary algorithm. Two evolutionary algorithms were applied: the genetic algorithm and evolutionary strategy. Furthermore, a method of generating a unitary matrix is presented which is used for the first time for this task. This method is in some aspects better than the previous ones. Finally, a comparison of all used techniques is shown in experiments.
|
|
|
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.
|
|
|
Optimization of PID controller using evolutionary computing techniques
Kočí, Jakub ; Matoušek, Radomil (referee) ; Lang, Stanislav (advisor)
This bachelor thesis deals with using evolutionary computation for tuning up PID controller. In research part there are summarised information about regulation and another background information about quality of regulation and ITAE criterion. Practical part consist of implementing three evolutionary computation algorithms - differential evolution, evolution strategy and genetic algorithm. These and MATLAB's function ga() are compared on two systems mutually and to Ziegler-Nichols rule. Basic comparsion is followed by statistical evaluation on second system.
|
|
|
New Evolutionary Algorithms for Designing Cellular Automata
Ormandy, Adam ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
This thesis describes an evolutionary design of state-transition functions in cellular auto- mata built on conditionally matching rules. It presents a new algorithm ESP and its com- parison with already existing evolutionary techniques, specifically the evolutionary strategy and genetic algorithm. Chosen Case studies include self-replicating structures, moving ob- jects and development of patterns.
|
|
|
The Impact of Candidate Solution Mappings on Evolutionary Algorithm Efficiency
Hrbáček, Jiří ; Korček, Pavol (referee) ; Křivánek, Jan (advisor)
The Concern of the present study is summarizing knowledges in the theory of mapping candidate solutions , analysis and application of evolutionary algorithms. The study provides summary of the evolutionary algorithms, classification and application. The target of the study is links gained knowledge from sectionS of ; evolutionary algorithms, mapping candidate solutions and creations of a system that will demonstrate and influence mapping the efficiency of the evolutionary algorithms succesfully.
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