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The Application of PSO in Business
Veselý, Filip ; Kaštovský, Petr (referee) ; Dostál, Petr (advisor)
This work deals with two optimization problems, traveling salesman problem and cluster analysis. Solution of these optimization problems are applied on INVEA-TECH company needs. It shortly describes questions of optimization and some optimization techniques. Closely deals with swarm intelligence, strictly speaking particle swarm intelligence. Part of this work is recherché of variants of particle swarm optimization algorithm. The second part describes PSO algorithms solving clustering problem and traveling salesman problem and their implementation in Matlab language.
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Particle Swarm Optimization Library
Hruban, Milan ; Strnadel, Josef (referee) ; Bidlo, Michal (advisor)
The aim of this thesis is to develop a library that is able to solve optimization tasks using PSO. The library is implemented using Kotlin and is designed to achieve high extensibility and usability. Moreover, a tool for processing and statistical analysis of experiments performed using the library is implemented by means of the Jupyter Notebook environment. The utilization of these tools creates a setup suitable for experimenting with the current and developing new variations of the PSO algorithm.
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Genetic Algorithms
Masárová, Mária ; Zbořil, František (referee) ; Zbořil, František (advisor)
This thesis deals with genetic algorithm, their terminology and use. It describes various problems that can be solved by using genetic algorithms. Different algorithms of swarm intelligence are also presented in this thesis, while firefly algorithm also serves to compare the efficiency between it and genetic algorithm. The main task of this thesis is to perform experiments with three optimization tasks, namely, travelling salesman problem, boolean satisfiability problem and searching for extreme in function.
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Disruption of movement or cohesion of groups through individuals
Vejmola, Jiří ; Neruda, Roman (advisor) ; Děchtěrenko, Filip (referee)
Title: Disruption of movement or cohesion of groups through individuals Author: Jiří Vejmola Department: Department of Theoretical Computer Science and Mathematical Logic Supervisor of the master thesis: Mgr. Roman Neruda, CSc., Institute of Computer Science of the ASCR, v. v. i. Abstract: Just a few of informed and like-minded individuals, guides, are needed to lead otherwise naive group. We look at some of the possible changes that can be caused by the presence of another informed individual with different intentions, an intruder. It is implied that he cannot cause anything significant under normal circumstances. To counter that and to increase his chances of success we intruduce a new parameter - credibility. We explore how it changes the overall behaviour. We show that by applying it to the intruder his influence over others increases. This in turn makes naive individuals more willing to follow him. We show that if the right conditions are met he can eventually become the one who leads the group. Keywords: multi-agent system, swarm intelligence, emergence, credibility
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Swarm Intelligence
Winklerová, Zdenka ; Šaloun, Petr (referee) ; Škrinárová,, Jarmila (referee) ; Zbořil, František (advisor)
The intention of the dissertation is the applied research of the collective ( group ) ( swarm ) intelligence . To demonstrate the applicability of the collective intelligence, the Particle Swarm Optimization ( PSO ) algorithm has been studied in which the problem of the collective intelligence is transferred to mathematical optimization in which the particle swarm searches for a global optimum within the defined problem space, and the searching is controlled according to the pre-defined objective function which represents the solved problem. A new search strategy has been designed and experimentally tested in which the particles continuously adjust their behaviour according to the characteristics of the problem space, and it has been experimentally discovered how the impact of the objective function representing a solved problem manifests itself in the behaviour of the particles. The results of the experiments with the proposed search strategy have been compared to the results of the experiments with the reference version of the PSO algorithm. Experiments have shown that the classical reference solution, where the only condition is a stable trajectory along which the particle moves in the problem space, and where the influence of a control objective function is ultimately eliminated, may fail, and that the dynamic stability of the trajectory of the particle itself is not an indicator of the searching ability nor the convergence of the algorithm to the true global solution of the solved problem. A search strategy solution has been proposed in which the PSO algorithm regulates its stability by continuous adjustment of the particles behaviour to the characteristics of the problem space. The proposed algorithm influenced the evolution of the searching of the problem space, so that the probability of the successful problem solution increased.
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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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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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Solving Optimization Tasks by PSO Algorithms
González, Marek ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
In this document we describe the Particle Swarm Optimization (PSO) and discuss its performance in solving optimization tasks. PSO is stochastic population-based computational method mainly focused on continuous optimization. We give an introduction to the field of optimization and provide a theoretical description of the PSO method. We have implemented the method in C/C++ and investigated the best working parameter set. The implementation is evaluated on clustering, travelling salesman problem, and function minimization case studies.
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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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