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Automotive antenna for mobile communications
Porč, Jan ; Láčík, Jaroslav (referee) ; Pokorný, Michal (advisor)
This thesis deals with design of flush–mounted planar disc antenna suitable for use in vehicles. For each of the bands GSM900 and GSM1800, which are used in Czech republic, an independent antenna has been created. As a simulator of the electromagnetic field the program IE3D has been used. For the improvement of theoretical results an optimisation in the program MATLAB has been developed. As the optimisation method the genetic algorithms have been selected.
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The use of genetic algorithm for edge detection in medical images
Slobodník, Michal ; Švrček, Martin (referee) ; Hrubeš, Jan (advisor)
This work deals with the possibilities of employing a genetic algorithm to edge detection. There is introduced a project which uses enhanced image divided into sub-regions, on which detection by genetic algorithm is applied. To achieving our goals are used individuals in two-dimensional bit arrays, for which are specially adjusted mutation and crossover operators. Cost minimization approach is used as fitness function. The project was created and tested in Matlab environment.
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Optimization of four-bar mechanism geometry for the predescribed trajectory
Korytár, Lukáš ; Sova, Václav (referee) ; Grepl, Robert (advisor)
This thesis deals with the optimization of arm lengths of four-bar RRRR mechanism using matrix kinematics. It compares and describes the methods, which are available in MATLAB software environment for this purpose. Consequently, an optimization algorithm using fmincon function is designed for which Monte-Carlo algorithm performs the first estimates. Elementary requirements for the proposed algorithm are devised in order to accurately duplicate the predescribed trajectory.
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Application of genetic algorithm for production scheduling of engineering company
Stariat, Jiří ; Skočdopolová, Veronika (advisor) ; Zouhar, Jan (referee)
This thesis is engaged in scheduling problem, his special types and methods of solving. Scheduling problem is a common operations research problem, which ranks among combinatorial problems. The aim of the scheduling problem is to assign certain activities and resources to individual time moments. Scheduling problem is NP-complete problem. Its computational complexity is thus so high, that there is currently no known algorithm that precisely solve its any instance in polynomial time. Is therefore used for its solution heuristics and metaheuristcs. In this thesis is described in detail metaheuristics of genetic algorithm. Application of genetic algorithm for production scheduling of specific engineering company is the main objective of this thesis.
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A method for selecting a portfolio of tools for online marketing activities and supporting their management
Smutný, Zdeněk ; Doucek, Petr (advisor) ; Stříteský, Václav (referee) ; Novotný, Ota (referee) ; Hynek, Josef (referee)
Online marketing activities play an increasingly important role for organization in connection with the development of internet based technologies and their positive reception by the society. The aim of this dissertation is to design an artefact that would support the decision making of marketing specialists and thus the management of online marketing activities. The starting point is an explorative research among Czech companies, which identifies the issues felt as problematic and the needs of the selected set of organizations. Introduced at the same time is the current state of use of selected tools for online marketing by these organizations, and the situation is compared with worldwide development. The output of this explorative research, the examination of scientific literature, and a critical analysis serve as a basis for designing an own method, Genoma, whose purpose is to support the decision making of marketing specialists, and thereby also the management of marketing activities in internet-mediated environment. This method is presented as Deming (PDCA) cycle, which enables it to be used not only separately, but also as part of other frameworks for the management of marketing activities (e.g. the frameworks PMF, MCPF and RACE, which are presented in the dissertation). The Genoma method uses mainly the genetic algorithm for selecting a suitable portfolio of online marketing tools for a particular campaign. The selection is made on the basis of expected feedback at the level of social interaction, meeting the given marketing targets, and the financial demands of the individual tools. The prerequisite of using this method is a knowledge base that includes the area of sociotechnical interaction, which is based on interpreting phenomena related to the internet-mediated environment and the features of complex networks. Methodically, this dissertation builds on the complementary relationship of the behavioural (social informatics) and the design type of research (design science research). The final assessment of the suitability of the proposed method is done on the basis of a multiple case study, which uses also an own program created in C#, implementing the genetic algorithm used in the Genoma method.
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Least squares method using genetic algorithm
Holec, Matúš ; Tichý, Vladimír (advisor) ; Šalamon, Tomáš (referee)
This thesis describes the design and implementation of genetic algorithm for approximation of non-linear mathematical functions using the least squares method. One objective of this work is to theoretically describe the basics of genetic algorithms. The second objective is to create a program that would be potentially used to approximate empirically measured data by the scientific institutions. Besides the theoretical description of the given subject, the text part of the work mainly deals with the design of the genetic algorithm and the whole application solving the given problem. Specific part of the assignment is that the developed application has to support approximation of points by various mathematical non-linear functions in several different intervals, and then it has to insure, that resulting functions are continuous throughout all the intervals. Described functionality is not offered by any available software.
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Heuristic and metaheuristic methods for travelling salesman problem
Burdová, Jana ; Kalčevová, Jana (advisor) ; Zouhar, Jan (referee)
Minimal length of a travelling salesman's problem had been studied in this diploma these. Travelling salesman must come trough each place just once and then go back to the starting place. This problem can be illustrated as a problem of graph theory, such that places are the vertices, roads are the edges, distances of roads are the lengths of edges. The optimal travelling salesman's problem tour is the shortest Hamiltionian cycle in the graph. It is a classical NP-complete problem. There is no algorithm that solves this problem in polynomial time. This problem can be solved by using various approximation algorithms, they offer less time consumption and lowest quality than optimization. This diploma these had been dedicated to approximation algorithms, for example: nearest neighbor method, minimal spanning tree method, Christofide's method, 2-opt., genetic algorithm, etc.
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Multiobjective portfolio analysis
Kunt, Tomáš ; Kalčevová, Jana (advisor) ; Kuncová, Martina (referee)
The objective of this thesis is to apply alternative multi-objective optimization techniques to the portfolio selection problem. Theoretical part starts with detailed analysis of the classical Markowitz model and its assumptions. Following that, introduction of multi-criterion optimization techniques available for finding non-dominated portfolios is given. One of these techniques, the genetic algorithm, is presented in great detail. Some of the basic methods useful for predicting stock prices and its risks are presented at the end of the theoretical part. Practical part presents an application of the theory to the problem of constructing efficient portfolios of 11 selected stocks traded on Prague Stock Exchange. Results achieved by different approaches are compared and interpreted.
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