National Repository of Grey Literature 14 records found  1 - 10next  jump to record: Search took 0.00 seconds. 
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.
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.
Ant Colony Optimization Algorithms for Shortest Path Problems - Java implementation
Dostál, Marek ; Miškařík, Kamil (referee) ; Matoušek, Radomil (advisor)
This diploma thesis deals with ant colony optimization for shortest path problems. In the theoretical part it describes Ant Colony Optimization. In the practical part ant colony optimization algorithms are selected for the design and implementation of shortest path problems in the Java.
Implementation of the Vehicle Routing Problem Using the Algorithm of Ant Colonies and Particle Swarms
Hanek, Petr ; Kubánková, Anna (referee) ; Šeda, Pavel (advisor)
This diploma thesis focuses on meta-heuristic algorithms and their ability to solve difficult optimization problems in polynomial time. The thesis describes different kinds of meta-heuristic algorithms such as genetic algorithm, particle swarm optimization or ant colony optimization. The implemented application was written in Java and contains ant colony optimization for capacitated vehicle routing problem and particle swarm optimization which finds the best possible parameters for ant colonies.
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.
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.
Interactive simulation by means of Flash technology
Látal, Pavel ; Šedá, Jitka (referee) ; Matoušek, Radomil (advisor)
This bachelor thesis is interested in designing of six interactive simulations by means of Flash technology. The presented interactive simulations are follows: an extended version of Conway’s cellular automata which was realized on orthogonal and hexagonal grid, simulation of 1D cellular automata, demonstration of selected selection principles of evolutionary algorithms, possible graphic representation of 2D Turing machine, and application for demonstration of ant colony behavior.
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.
Implementation of the Vehicle Routing Problem Using the Algorithm of Ant Colonies and Particle Swarms
Hanek, Petr ; Kubánková, Anna (referee) ; Šeda, Pavel (advisor)
This diploma thesis focuses on meta-heuristic algorithms and their ability to solve difficult optimization problems in polynomial time. The thesis describes different kinds of meta-heuristic algorithms such as genetic algorithm, particle swarm optimization or ant colony optimization. The implemented application was written in Java and contains ant colony optimization for capacitated vehicle routing problem and particle swarm optimization which finds the best possible parameters for ant colonies.
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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