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Creating Timetables Using Genetic Algorithms
Horký, Aleš ; Matoušek, Jiří (referee) ; Minařík, Miloš (advisor)
This bachelor thesis contains design and implementation of two-phase genetic algorithm intended for creating timetable schedules at primary schools. The algorithm is designed for maximum reduction of state space of solved problem without decrease of its universality. The implementated program in C++ language is applicable for creating timetable schedules at small and medium sized schools.
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Optimization of cogeneration system
Stacha, Radek ; Turek, Vojtěch (referee) ; Jegla, Zdeněk (advisor)
Master thesis is focused on optimization of cogeneration system for purpose of rating optimization methods and evaluating properties of these methods. For each method there is description together with block schemes. First part of thesis is devoted to description of methods and their comparison. Second part consists of development of hybrid algorithm, which is used to optimize cogeneration systém model. Each algorithm compared is together with hybrid algorithms included in annexes.
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Hybrid Algorithms in Optimization
Zamazal, Petr ; Hrabec, Pavel (referee) ; Popela, Pavel (advisor)
This work deals with the solution of an integer programming task using a hybrid algorithm. Mentioned task is a minimum cost network flow problem with option of adding new edges. The hybrid algorithm is based on a genetic algorithm using the network simplex method. Implementation is in the Python programming language.
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New Hybrid Methods for Robust and Automated Parameter Estimation of Mechatronic Systems
Najman, Jan ; Štefek, Alexandr (referee) ; Opluštil, Vladimír (referee) ; Grepl, Robert (advisor)
The thesis deals with the development of a new hybrid optimization algorithm for mechatronic models. The introductory chapters are devoted to a general description of the problem of estimating unknown system parameters, based on the developed mathematical model and measured data. Furthermore, an overview and a brief description of available optimization algorithms that are suitable for solving this type of problem is given. Based on the research study, the specific objectives of the paper are then formulated. In the second part of the thesis, a newly developed set of mechatronic models created using physical modelling tools is described. Subsequently, a comparative test of the speed and success rate of the selected optimization algorithms is performed using these models. Based on the results of this test, the design of a new hybrid algorithm is proposed, which is then tested and compared with the other algorithms. Finally, several new auxiliary functions and tools are presented to detect and analyze improperly designed parameter estimation problems.
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Hybrid Algorithms in Optimization
Zamazal, Petr ; Hrabec, Pavel (referee) ; Popela, Pavel (advisor)
This work deals with the solution of an integer programming task using a hybrid algorithm. Mentioned task is a minimum cost network flow problem with option of adding new edges. The hybrid algorithm is based on a genetic algorithm using the network simplex method. Implementation is in the Python programming language.
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|
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Creating Timetables Using Genetic Algorithms
Horký, Aleš ; Matoušek, Jiří (referee) ; Minařík, Miloš (advisor)
This bachelor thesis contains design and implementation of two-phase genetic algorithm intended for creating timetable schedules at primary schools. The algorithm is designed for maximum reduction of state space of solved problem without decrease of its universality. The implementated program in C++ language is applicable for creating timetable schedules at small and medium sized schools.
|
|
|
Optimization of cogeneration system
Stacha, Radek ; Turek, Vojtěch (referee) ; Jegla, Zdeněk (advisor)
Master thesis is focused on optimization of cogeneration system for purpose of rating optimization methods and evaluating properties of these methods. For each method there is description together with block schemes. First part of thesis is devoted to description of methods and their comparison. Second part consists of development of hybrid algorithm, which is used to optimize cogeneration systém model. Each algorithm compared is together with hybrid algorithms included in annexes.
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