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Řešení optimální cesty svozu odpadů pomocí rojové inteligence
VÁCHA, Ladislav
This work is focused on problem-solving nondeterministically polynomial (NP) complexity using ant colony optimization. The work is divided into three blocks. The first is approximated aforementioned optimization along with some modifications. The second part focuses on the problems themselves, in this case, the traveling salesman problem (TSP), from which the vehicle routing problem (VRP). The final part of this thesis describes the use of these tools for the collection of separated waste for district of the České Budějovice.
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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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Solving Optimization Tasks by ACO Algorithms
Habrnál, Matěj ; Samek, Jan (referee) ; Zbořil, František (advisor)
The presented thesis puts its main focus on the basic optimization algorithms ACO (Ant Colony Optimization) and their development and seeks the inspiration in the ants live. The aim is to demonstrate the activity of these algorithms on optimization problems - the traveling salesman problem and the finding food sources problem and optimal routes between an anthill and food. The thesis also describes experiments that try to determine the influence of adjustable parameters of ant algorithms. First, ACO algorithms theory is described followed then by the application of these algorithms on both selected optimization problems. The conclusion sums up experiments analysis with established applications and evaluating prospective results.
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Comparison of Methods for Travelling Salesman Problem
Šušová, Lucia ; Janoušek, Vladimír (referee) ; Rozman, Jaroslav (advisor)
This work is about comparison of methods for solving the traveling salesman problem. There are many algorithms for finding solution of this NP complete problem but it is not easy to choose the right one. Main goal of this thesis is experimental methods comparison between each other. Reader is going to learn what result she can expect if she chooses certain algorithm for finding the path. First part is focused on theoretical basics where is described all needed information for understanding the problem. Second part describes single heuristics and methods for solving these problems. The methods are divided into groups by principle of working. Next part contains experimental comparison of methods. This comparison was done based on own implementation of single heuristics. The following part of this work contains information about this implementation and also describes comparison application. Next possible steps of this project are described in conclusion.
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Solving of Optimisation Tasks Inspired by Living Organisms
Popek, Miloš ; Peringer, Petr (referee) ; Martinek, David (advisor)
We meet with solving of optimization problems every day, when we try to do our tasks in the best way. An Ant Colony Optimization is an algorithm inspired by behavior of ants seeking a source of food. The Ant Colony Optimization is successfuly using on optimization tasks, on which is not possible to use a classical optimization methods. A Genetic Algorithm is inspired by transmision of a genetic information during crossover. The Genetic Algorithm is used for solving optimization tasks like the ACO algorithm. The result of my master's thesis is created simulator for solving choosen optimization tasks by the ACO algorithm and the Genetic Algorithm and a comparison of gained results on implemented tasks.
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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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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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