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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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Evolutionary Optimisation of Analogue Circuits
Mihulka, Tomáš ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
The aim of this work was to create a system for optimisaton of specific analog circuits by evolution using multiple fitness functions . A set of experiments was run, and the results analyzed to evaluate the feasibility of evolutionary optimisation of analog circuits . A requirement for this goal is the study and choice of certain types of analog circuits and evolutionary algorithms . For the scope of this work , amplifiers and oscillators were chosen as target circuits , and genetic algorithms and evolutionary strategies as evolutionary algorithms . The motivation for this work is the ongoing effort to automate the design and optimisation of analog circuits , where evolutionary optimisation is one of the options .
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Toolbox for multi-objective optimization
Marek, Martin ; Hurák,, Zdeněk (referee) ; Kadlec, Petr (advisor)
This paper deals with multi-objective optimization problems (MOOP). It is explained, what solutions in multi-objetive search space are optimal and how are optimal (non-dominated) solutions found in the set of feasible solutions. Afterwards, principles of NSGA-II, MOPSO and GDE3 algorithms are described. In the following chapters, benchmark metrics and problems are introduced. In the last part of this paper, all the three algorithms are compared based on several benchmark metrics.
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Diagnostics of the state of the machine/machine components with the help of fuzzy sets
Horák, Roman ; Zuth, Daniel (referee) ; Marada, Tomáš (advisor)
Diploma thesis deals with the use of fuzzy logic in the field of technical diagnostics. The thesis is divided into theoretical and practical parts. The theoretical part describes technical diagnostics, fuzzy logic and genetic algorithm. The theoretical part is followed by a practical part in which fuzzy logic is tested on the Iris dataset and then the acquired knowledge is applied to a technical dataset evaluating machine fault conditions. At the end of the chapters of both datasets, the results are summarized and evaluated. The last chapter of the practical part is devoted to the description of the developed scripts in software Matlab 2022b. Part of the work are attachments in which the created FIS models and written scripts are stored.
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Moderní evoluční algoritmy pro hledání oblastí s vysokou fitness
Káldy, Martin ; Holeňa, Martin (advisor) ; Gemrot, Jakub (referee)
Evolutionary algorithms are optimization techniques inspired by the actual evolution of biological species. They use conceptually simple process of two repeating phases of reproduction and fitness-based selection, that iteratively evolves each time better solutions. Evolutionary algorithms receive a lot of attention for being able to solve very hard optimization problems, where other optimization techniques might fail due to existence of many local optima. Wide range of different variants of evolutionary algorithms have been proposed. In this thesis, we will focus on the area of Estimation of Distribution Algorithms (EDA). When creating the next generation, EDAs transform the selected high-fitness population into a probability distribution. New generation is obtained by sampling the estimated distribution. We will design and and implement combinations of existing EDAs that will operate in business-specific environment, that can be characterized as tree-like structure of both discrete and continuous variables. Also, additional linear inequality constraints are specified to applicable solutions. Implemented application communicates with provided interfaces, retrieving the problem model specification and storing populations into database. Database is used to assign externally computed fitness values from...
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Parallel genetic algorithm
Trupl, Jan ; Kobliha, Miloš (referee) ; Jaroš, Jiří (advisor)
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.
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Optimization of Processes in Logistics with Visualization Support
Kršák, Martin ; Bidlo, Michal (referee) ; Křivka, Zbyněk (advisor)
The master thesis aims to design, implement, and compare algorithms that optimize processes in logistics, mainly in the planning phase. Heuristics and approximation genetic algorithms will find an near-optimal solution to NP-hard problem, such as the traveling salesman problem, with a delay less than several hours. The role of this algorithm is to plan an efficient route for garbage trucks that collect and distribute large-scale waste to waste yards in a specific city. The goal of the optimization is to minimize the shipping costs.
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Evolutionary Analogue Amplifier Optimisation
Bielik, Marek ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
Táto práca demonštruje možnosti využitia evolučných algoritmov, konkrétne evolučných stratégií, v doméne dizajnu analógových zosilňovačov. Do implementácie je zahrnutý ngSPICE simulátor, ktorý je použitý na vyhodnotenie optimalizovaných riešení a v práci je navrhnutých niekoľko vyhodnocovacích metód. Práca tiež zahŕňa experimenty a ich výsledky, ktoré boli použité na určenie najvodnejších parametrov evolučných stratégií. Cieľom bolo optimalizovať hodnoty súčiastok jedno a dvoj stupňových zosilňovačov s bipolárnymi tranzistormi v zapojení so spoločným emitorom. Výsledkom je nástroj umožňujúci návrh zosilňovačov s ľubovoľným zosilnením v rámci možností daného obvodu bez použitia akéhokoľvek matematického aparátu.
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Evolutionary Optimisation of Analogue Circuits
Mihulka, Tomáš ; Zachariášová, Marcela (referee) ; Bidlo, Michal (advisor)
The aim of this work was to create a system for optimisaton of specific analog circuits by evolution using multiple fitness functions . A set of experiments was run, and the results analyzed to evaluate the feasibility of evolutionary optimisation of analog circuits . A requirement for this goal is the study and choice of certain types of analog circuits and evolutionary algorithms . For the scope of this work , amplifiers and oscillators were chosen as target circuits , and genetic algorithms and evolutionary strategies as evolutionary algorithms . The motivation for this work is the ongoing effort to automate the design and optimisation of analog circuits , where evolutionary optimisation is one of the options .
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Moderní evoluční algoritmy pro hledání oblastí s vysokou fitness
Káldy, Martin ; Holeňa, Martin (advisor) ; Gemrot, Jakub (referee)
Evolutionary algorithms are optimization techniques inspired by the actual evolution of biological species. They use conceptually simple process of two repeating phases of reproduction and fitness-based selection, that iteratively evolves each time better solutions. Evolutionary algorithms receive a lot of attention for being able to solve very hard optimization problems, where other optimization techniques might fail due to existence of many local optima. Wide range of different variants of evolutionary algorithms have been proposed. In this thesis, we will focus on the area of Estimation of Distribution Algorithms (EDA). When creating the next generation, EDAs transform the selected high-fitness population into a probability distribution. New generation is obtained by sampling the estimated distribution. We will design and and implement combinations of existing EDAs that will operate in business-specific environment, that can be characterized as tree-like structure of both discrete and continuous variables. Also, additional linear inequality constraints are specified to applicable solutions. Implemented application communicates with provided interfaces, retrieving the problem model specification and storing populations into database. Database is used to assign externally computed fitness values from...
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