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Optimalization of Power Electric Engineering Processes by Genetic Algorithms
Paar, Martin ; Hradílek, Zdeněk (referee) ; Skala, Petr (referee) ; Toman, Petr (advisor)
Current trends in regulation of electricity supply continuity in the power engineering industry includes introduction of systems and customers standards. The electricity market liberalization in the European Union is speeded up the process furthermore. Companies included in the distribution network bussiness therefore began to be interested more in the evaluation of risks associated with the aplication of these standards. The aim of the thesis is to minimize the expenses caused by power losses of the distribution network by means of distribution network reconfiguration depending on the standard selection. For the minimization two of the Genetic algorithms was selected. As an criterion the overall expenses caused by power losses and the expenses caused by an electricity shortage. Furthermore the influence of the inclusion of the power loss to the calculation on the operation costs for given regulation standards. Two contemporary standards - finish and portugues - are considered together with three experimental standards. The aim of including experimental standards is to complete the regulation standards with parameters uncovered in the portuguese and finish standard. The results described in the thesis can be used in the distribution network optimization process from the point of reliability and operational costs.
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Heuristic Algorithms in Optimization
Komínek, Jan ; Šeda, Miloš (referee) ; Roupec, Jan (advisor)
This diploma thesis deals with genetic algorithms and their properties. Particular emphasis is placed on finding the influence of mutation and population size. Genetic algorithms are applied on inverse heat conduction problems (IHCP) in the second part of the thesis. Several different approaches and coding methods were tested. Properties of genetic algorithms were improved by definition of two new genetic operators – manipulation and sorting. Reported theoretical findings were tested on the real data of inverse heat conduction problem. The library for easy implementation of GA for solving general optimization problems in C ++ was created and is described in the last chapter.
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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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Genetic Algorithms and Scheduling
Škrabal, Ondřej ; Popela, Pavel (referee) ; Roupec, Jan (advisor)
This work deals with scheduling problem in particular plastic production service. The solution is based on heuristic algorithms, programming languages C + +, C # and is built on the .NET framework and LINQ to XML. It provides the users with comparisons of the heuristic approach with genetic algorithms applied to production problem. All methods results are compared in relation to hand-arranged plans.
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Genetic Algorithms - Multi-core CPU Implementation
Studnička, Vladimír ; Kuba, Martin (referee) ; Matoušek, Radomil (advisor)
his diploma thesis deals with creating the most universal library of genetic algorithms in C++, as much as possible, implemented with the certain number of universal operators, and then with testing created library on some examples. Library must support multi-core processors, implementation will be done over OpenMP. The library will be tested on three examples in all. The first two examples are mathematical functions, that are used just for genetic algorithms testing. Last problem for test is N-Queens problem. Finally we will use genetic algorithms to try find solution for Eternity II puzzle, there is declared a 2 million bounty for full solution.
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MES systems
Štrublíková, Iva ; Kantor, Tomáš (referee) ; Simeonov, Simeon (advisor)
The content of the diploma thesis is a description of the functions and features of the production control systems - MES (manufacturing execution systems), an analysis of these systems implemented in The Czech Republic, an elaboration of the system proposal of an intelligent production control system and retrieving new algorithms and functions according to which these systems can by formed. The MES systems analysis is performed by comparing implemented systems to the modules of production control systems conformably to MESA international. In the system suggestion there will be the intelligent component formed by automatic analysis of the effect of the order delay in production - automatic Gantt chart comparison of the plan versus reality. According to the adjusted system parameters it will separately make decisions about production scheduling. Searching new algorithms and functions will proceed in the reagions of artificial intelligence - genetic algorithms, holonic and multiagent systems, experts systems.
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The Comparison of the Algorithms for the Solution of Travel Sales Problem
Kopřiva, Jan ; Všetička, Martin (referee) ; Dostál, Petr (advisor)
The Master Thesis deals with logistic module innovation of information system ERP. The principle of innovation is based on implementation of heuristic algorithms which solve Travel Salesman Problems (TSP). The software MATLAB is used for analysis and tests of these algorithms. The goal of Master Thesis is the comparison of selections algorithm, which are suitable for economic purposes (accuracy of solution, speed of calculation and memory demands).
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