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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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The Use of Artificial Intelligence in Business
Matus, Gabriel ; Doskočil, Radek (referee) ; Dostál, Petr (advisor)
This work deals with traveling salesman problem (TSP) and examines it’s possibilities to use in business. It is about the optimization of the travel cost, saving time and unnecessary mileage. Part of the work is a program with a GUI written in program MATLAB. Program uses neural networks to calculate the most effective path between places, where the trader has to reach. It’s possible to use the algorithm for many purposes, e.g. distribution of goods, store management, planning of PCBs or rescue services. Program communicates with the Google Maps API server, which provides the actual information of the path.
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Optimization Using Ant Algorithms
Válek, Matěj ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
This bachelor thesis will deal with various applications of ant colony optimisation. In particular, Ant Colony System will be applied on the optimisation of traveling salesman problem and the design of rules for the development of cellular automata. The obtained results will be statistically analysed. Moreover, a GUI-based application has been developed which allows to interactively observe the progress of Ant Colony System for the educational purposes.
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Quantum-Inspired Optimisation Algorithms
Kosík, Dominik ; Sekanina, Lukáš (referee) ; Bidlo, Michal (advisor)
The focus of this work is an implementation of the chosen quantum-inspired optimisation algorithm and its modifications, which will be compared at the end of the work. As the optimisation algorithm was chosen simulated quantum annealing algorithm. The first part of the work will lay the theoretical groundwork of standard optimisation algorithms used in this work, physics from which the inspiration for the simulated quantum annealing originates, and a description of the chosen algorithm. The second part will focus on the implementation of the algorithms on the selected problems. The selected problems are travelling salesman problem, searching rules for cellular automaton and MAX-SAT problem. The last part will contain the proposed modifications of the simulated quantum annealing, a comparison of the basic variant and standard optimisations algorithms, and an evaluation of the results.
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Risk modelling for production processes
Ftáčnik, Peter ; Bednář, Josef (referee) ; Popela, Pavel (advisor)
The processes and procedures covered the main core of the professional operations in the manufacturing plant. The enterprise should focus on the efficient running of the main processes and risks associated with these procedures. My thesis deals with the risk analysis of selected manufacturing processes particular company from qualitative and quantitative point of view. First, the results are presented from qualitative risk analysis, especially in scope of failures of the machines or in the sequences of production. Second part focus on the problems of optimization sequence batches that the total time required for pre-setting of machines between doses should be minimal. The thesis also takes random waiting period into the consideration and applies wait-and-see approach of stochaistic programming applied in task traveling salesman. Calculations are processed by the GAMS. The results from the GAMS are refered in MS Excel, they are further discussed and interpreted by using descriptive statistics.
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Integer Optimization for Transportation Problems
Cabalka, Matouš ; Žák, Libor (referee) ; Popela, Pavel (advisor)
The thesis deals with optimization models in transportation problems with emphasis on traveling salesman problem. Brief introduction to the history is followed by theoretical part describing linear programming, integer programming and formulation of traveling salesman problem. Description of data preprocessing is included. Finally computational results are discussed and evaluated.
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Advanced Evolutionary Optimisation of TSP-Based Problems
Hladyuk, Vadym ; Vašíček, Zdeněk (referee) ; Bidlo, Michal (advisor)
This paper solves the traveling salesman problem using an evolutionary algorithm, specifically a genetic algorithm. It is a hybrid of the genetic algorithm, using a local search algorithm and other enhancements that further improve the results obtained. The traveling salesman problem will be solved from 20 cities to 25,000 cities. In the experiments chapter, I have determined the best settings for all the parameters in the program and properly tested their appropriateness. In the next part of the experiments chapter, I found out the performance of the full version of the genetic algorithm and its variants. In the last section, I compared the evolution of fitness values of different variants of genetic algorithms and different variants of crossover operators, I also compared the time consumption. I suggested further possible improvements either to the local search algorithm or to another approach to solve the TSP.
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Quantum-Inspired Optimisation Algorithms
Kosík, Dominik ; Sekanina, Lukáš (referee) ; Bidlo, Michal (advisor)
The focus of this work is an implementation of the chosen quantum-inspired optimisation algorithm and its modifications, which will be compared at the end of the work. As the optimisation algorithm was chosen simulated quantum annealing algorithm. The first part of the work will lay the theoretical groundwork of standard optimisation algorithms used in this work, physics from which the inspiration for the simulated quantum annealing originates, and a description of the chosen algorithm. The second part will focus on the implementation of the algorithms on the selected problems. The selected problems are travelling salesman problem, searching rules for cellular automaton and MAX-SAT problem. The last part will contain the proposed modifications of the simulated quantum annealing, a comparison of the basic variant and standard optimisations algorithms, and an evaluation of the results.
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