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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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Vybrané problémy související s vehicle routing
Kuklis, Imrich ; Pergel, Martin (advisor) ; Surynek, Pavel (referee)
In our thesis we concentrate on a well-known problem which is popular among the scientists from the field of logistics, theoretical computer science and applied mathematics. This problem is called the Vehicle Routing Problem. We concentrate mainly on the Vehicle Routing Problem with Time Window. We implement some scheduling algorithms and compare their results. Powered by TCPDF (www.tcpdf.org)
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Polynomial time primality testing
Bednaříková, Alžběta ; Žemlička, Jan (advisor) ; Čech, Martin (referee)
The topic of my thesis is the testing of prime numbers in polynomial time. The text focuses on the specific algorithm published in 2002 by Manindra Agrawal, Neeraj Kayal and Nitin Saxena and it is known as the AKS primality test. In the introduction of this work, important properties and concepts essential for the text understanding are revised. Then the basic idea of the test is explained. The description of the algorithm itself continues. The aim of the work is to prove the Theorem on the correctness of the AKS test from a gradually built-up theory and to calculate the time complexity of the algorithm. Finally, it is proved that the calculated time complexity is polynomial.
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Porovnání výpočetní složitosti vybraných algoritmů pro dolování znalosti z dat
Matzke, Miroslav
Matzke, M. Comparison of Computational Complexity of Selected Data Mining Algorithms, Diploma Thesis. Brno, 2018. This diploma thesis deals with the comparison of the time complexity and the success of the classification of selected algorithms for mining knowledge from data with focus on neural networks and optimal settings for work execution. In the theoretical part, it is essential to get acquainted with the distribution of algorithms, their functionality and complexity. Then follows the selection of algorithms with focus on neural networks and their settings, especially hidden layers, momentum and learning rate. Another part deals with data used for experimental testing, which are both nominal and numerical data, and also real or generated. Also included is the accuracy of measurement and performance measurement of the two assemblies used to test individual experiments. The third part is the testing of the time complexity and the percentage success of the algorithms and the output especially in graphical form followed by analysis and recommendations from the results with focus on the optimal setting against the automatic and initial settings.
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Vybrané problémy související s vehicle routing
Kuklis, Imrich ; Pergel, Martin (advisor) ; Surynek, Pavel (referee)
In our thesis we concentrate on a well-known problem which is popular among the scientists from the field of logistics, theoretical computer science and applied mathematics. This problem is called the Vehicle Routing Problem. We concentrate mainly on the Vehicle Routing Problem with Time Window. We implement some scheduling algorithms and compare their results. Powered by TCPDF (www.tcpdf.org)
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Particular Problems Related to the Vehicle Routing Problem
Kuklis, Imrich ; Pergel, Martin (advisor) ; Majerech, Vladan (referee)
Title: Particular Problems Related to the Vehicle Routing problem Author: Imrich Kuklis Department: Department of Software and Computer Science Education Supervisor: RNDr. Martin Pergel, Ph.D., Department of Software and Computer Science Education Abstract: In this thesis we present and implement some scheduling algorithms. In the first part we discuss the vehicle routing problem and its variants. In the second part we describe the algorihms we used in the thesis. In the third part we compare the algorithm by their results on several tests. In the last chapter we describe the documentation of the programs which we implemented and discuss the possible future extension of the thesis. Powered by TCPDF (www.tcpdf.org)
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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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