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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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Swarm Intelligence Based Experiment in RDS
Kolář, Ladislav ; Florián, Tomáš (referee) ; Honzík, Petr (advisor)
The thesis consists of two parts. In the first one the overview of robotic simulators is compiled with more detailed focus on the Microsoft Robotics Developer Studio (MRDS). The process of development of the new project including both programming languages C# and Visual Programming Language (VPL) is described in form of manual. The second part of the thesis is aimed to explain the term swarm intelligence, to describe the concrete experiment and to implement it in MRDS. Finally the achieved results are summarized and discussed.
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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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Artificial Life Models
Ďuričeková, Daniela ; Martinek, David (referee) ; Peringer, Petr (advisor)
This bachelor thesis describes design and implementation of an artificial life simulator. The work is divided into four parts. The aim of the first part is to provide a brief overview of artificial life and related terminology. The second part deals with selected design patterns and the process of designing a simulation system, whose purpose is to simulate an ecosystem of artificial life entities. The subsequent part focuses on implementation of individual system components. Finally, the system is tested and evaluated on two sample models.
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Experiments with the Swarm Intelligence
Hula, Tomáš ; Zbořil, František (referee) ; Grulich, Lukáš (advisor)
This work deals with the issue of swarm intelligence as a subdiscipline of artificial intelligence. It describes biological background of the dilemma briefly and presents the principles of searching paths in ant colonies as well. There is also adduced combinatorial optimization and two selected tasks are defined in detail: Travelling Salesman Problem and Quadratic Assignment Problem. The main part of this work consists of description of swarm intelligence methods for solving mentioned problems and evaluation of experiments that were made on these methods. There were tested Ant System, Ant Colony System, Hybrid Ant System and Max-Min Ant System algorithm. Within the work there were also designed and tested my own method Genetic Ant System which enriches the basic Ant System i.a. with development of unit parameters based on genetical principles. The results of described methods were compared together with the ones of classical artificial intelligence within the frame of both solved problems.
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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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Robot path planning by means of ant algorithms
Pěnčík, Martin ; Krček, Petr (referee) ; Dvořák, Jiří (advisor)
This thesis deals with robot path planning. It contains an overview of general approaches for path planning and describes methods of swarm intelligence and their application for robot path planning. This paper also contains proposals of adjustments for ant algorithms and it presents experimental results of algorithm implementation.
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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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Swarm Intelligence in MRDS
Kučera, Lukáš ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
The background research in this Master’s thesis is focused on swarm intelligence. Further, there are two experiments described. They are based on released publications and they study behaviour of a group of robots during a puck gathering and during a target search. The actual thesis follows a repetition of these experiments in Microsoft Robotics Developer Studio (RDS), a free robotics simulation environment. The realization of both experiments in RDS is documented in detail and the achieved results are evaluated and compared with the results described in the publications. In conclusion, the thesis summarizes basic features, advantages and disadvantages of developing in RDS, based on a personal experience.
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