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Robot path planning by means of swarm intelligence
Schimitzek, Aleš ; Krček, Petr (referee) ; Dvořák, Jiří (advisor)
This diploma thesis deals with the path planning by swarm intelligence. In the theoretical part it describes the best known methods of swarm intelligence (Ant Colony Optimization, Bee Swarm Optimization, Firefly Swarm Optimization and Particle Swarm Optimization) and their application for path planning. In the practical part particle swarm optimization is selected for the design and implementation of path planning in the C#.
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Novel Applications of Ant Algorithms
Korgo, Jakub ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
Ant algorithms have been used for a variety of combinatorial optimization problems. One of these problems, where ant algorithms haven't been used, is the design of transition rules for cellular automata (CA). Which is a problem that this master's thesis is focused on. This work begins with an introduction into ant algorithms and a overview of its applications, followed by an introduction into CA. In the next part the author proposes a way how to encode rules of CA into a graph which is used in ant algorithms. The last part of this thesis contains an application of encoded graph on elitist ant system and MAX-MIN ant system. This is followed by experimental results of creating transition rules for CA problems by these algorithms.
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Applications of Ant Algorithms
Kaščák, Imrich ; Vašíček, Zdeněk (referee) ; Bidlo, Michal (advisor)
The presented thesis focuses on the basic optimization algorithm of Ant Colony Optimization (ACO) - Ant System (AS) and its extension, Ant Colony System (ACS) on Traveling Salesman Problem (TSP). The essence of these algorithms is to find the optimal solution (the shortest path) in a specified instance containing several locations. The thesis demonstrates verification of behaviour of both algorithms, experimental study of impact of adjustable parameters of ant algorithms on result. Furthermore, the thesis is focused on examining the idea of optimizing detection of image edges by introducing a modification into an existing solution. Modified solution experiments are performed and compared to the original.
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Large-Scale Travelling Salesman Problem
Kukula, Lukáš ; Žaloudek, Luděk (referee) ; Bartoš, Pavel (advisor)
Thesis deals with solving large-scale traveling salesman problem. The aim is to find the best possible solution within a short time. Most widely used heuristics was compared and most efficient proved to be Lin-Kernighan. This heuristic combined with the stochastic algorithm brings even better results than the Lin-Kernighan heuristic itself.
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Traveling Salesman Problem
Šůstek, Martin ; Snášelová, Petra (referee) ; Zbořil, František (advisor)
This thesis is focused on modification of known principles ACO and GA to increase their performance. Thesis includes two new principles to solve TSP. One of them can be used as an initial population generator. The appendix contains the implementation of the application in Java. The description of this application is also part of the thesis. One part is devoted to optimization in order to make methods more efficient and produce shorter paths. In the end of the thesis are described experiments and their results with different number of places from 101 up to 3891.
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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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Metrics and Criteria for Socio-Technical System Diagnostic
Raudenská, Lenka ; Dohnal, Mirko (referee) ; Nenadál, Jaroslav (referee) ; Fiala, Alois (advisor)
This doctoral thesis is focused on metrics and the criteria for socio-technical system diagnostics, which is a high profile topic for companies wanting to ensure the best in product quality. More and more customers are requiring suppliers to prove reliability in the production and supply quality of products according to given specifications. Consequently the ability to produce quality goods corresponding to customer requirements has become a fundamental condition in order to remain competitive. The thesis firstly lays out the basic strategies and rules which are prerequisite for a successful working company in order to ensure provision of quality goods at competitive costs. Next, methods and tools for planning are discussed. Planning is important in its impact on budget, time schedules, and necessary sourcing quantification. Risk analysis is also included to help define preventative actions, and reduce the probability of error and potential breakdown of the entire company. The next part of the thesis deals with optimisation problems, which are solved by Swarm based optimisation. Algorithms and their utilisation in industry are described, in particular the Vehicle routing problem and Travelling salesman problem, used as tools for solving specialist problems within manufacturing corporations. The final part of the thesis deals with Qualitative modelling, where solutions can be achieved with less exact quantitative information of the surveyed model. The text includes qualitative algebra descriptions, which discern only three possible values – positive, constant and negative, which are sufficient in the demonstration of trends. The results can also be conveniently represented using graph theory tools.
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Strategic Game in Multi-Agent System Jason
Vais, Roman ; Zbořil, František (referee) ; Král, Jiří (advisor)
This thesis describes artificial inteligence used in developement of computer games, particularly discusses with theory behing artificial inteligence used in real-time strategy games. It deals with implementation of extensions for one such a game. It analyzes posibylities of use multi-agent systems architecture for purposess of artificial inteligence in games. It describes concept of swarm inteligence as suitable but not used tool for developing not only videogame artificial inteligence. Moreover it attempts to find suitable representation of sensation for software agents and shows the difficulties of this task.
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