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Optimization of concrete structures using stochastic optimization methods
Slowik, Ondřej ; Pukl,, Radomír (referee) ; Novák, Drahomír (advisor)
The thesis focuses the reader on the sense of optimization and its importance for civil engineering. It outlines the principles used by some optimization methods and discusses the possibility of combination of any type of methods LHS with other optimization method. The result is a new type of optimization method named Nested LHS described in the text of the third chapter. The fifth chapter applies some of the lessons learned to solve practical optimization problem - reinforced concrete bridge solved by nonlinear finite element analysis using pseudostochastic optimization method LHS mean.
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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.
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Large-Scale Travelling Salesman Problem
Kukula, Lukáš ; Žaloudek, Luděk (referee) ; Bartoš, Pavel (advisor)
Thesis deals with solving large-scale traveling salesman problem. The aim is to find the best possible solution within a short time. Most widely used heuristics was compared and most efficient proved to be Lin-Kernighan. This heuristic combined with the stochastic algorithm brings even better results than the Lin-Kernighan heuristic itself.
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MATLAB/ Global Optimization Toolbox: Solving Optimization Problems
Švihálková, Kateřina ; Dvořák, Jiří (referee) ; Lang, Stanislav (referee) ; Matoušek, Radomil (advisor)
The bachelor thesis deals with basic description of global optimization methods which are implemented in MATLAB environment. First part of this thesis describes two MATLAB's toolboxes -- Optimization Toolbox and Global Optimization Toolbox. This study also describes chosen algorithms from those toolboxes (Genetic Algorithms, Simulated Annealing, Pattern Search and Fminsearch) and describes it's implementation. The last part is focused on the solving of optimization problems. Rosenbrock's function, Rastrigin's function, Traveling Salesman Problem and Stepped Cantilever Beam Design Problem are being solved by methods mentioned above. Reached results of every task are compared to each other and evaluated.
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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.
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Implementation and testing of selected optimization methods for the parameter estimation of simulation models
Zapletal, Marek ; Matoušek, Radomil (referee) ; Grepl, Robert (advisor)
This thesis deals with design of appropriate optimization algorithms for purposes of newly developed tool Mechlab’s parameter estimation, which serves for parameter estimation of simulation models in Matlab/Simulink. Levenberg-Marquardt algorithm had been chosen among other gradient methods. On the other hand, genetic algorithm and simulated annealing had been chosen from category of soft computing techniques to be implemented. Chosen algorithms were tested on artifical problem of mechanical oscilator and also on real datasets from electronic throttle. Proposed simulated annealing worked in both cases whith sufficient results, nevertheless was time-costly. For the oscilator problem, all the algorithms provided accurate solutions, but in the case of real dataset, Levenberg-Marquardt functionality was limited, while genetic algorithm still provided excelent results.
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Theory and Applications of Monte Carlo Methods
Hruda, Petr ; Šimek, Václav (referee) ; Bidlo, Michal (advisor)
This bachelor thesis deals with applications of Monte Carlo methods on various problems. In particular, Metropolis algorithm and Simulated Annealing were applied on optimization of Traveling Salesman Problem and the problem of graph coloring. Moreover, "traditional" Monte Carlo approach was utilized for statistical analysis of electronic circuits in which the values of components exhibit random variations with a given tolerance. The results are evaluated for different setups of Monte Carlo methods.
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