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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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Client-server search engine for optimal public transport routes
Brát, Daniel ; Hošek, Jiří (referee) ; Myška, Vojtěch (advisor)
This bachelor thesis deals with the design and implementation of a client-server based program for finding the optimal path in public transport networks. Theoretical basics describe the Traveling salesman problem and mention some methods for finding its solution. This chapter is followed by a theoretical design of the application itself. Next chapter describes chosen technologies to be used. The last chapter describes the realization of the application itself. Reached goals are described in the conclusion.
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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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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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Theory and Applications of Monte Carlo Methods
Hruda, Petr ; Šimek, Václav (referee) ; Bidlo, Michal (advisor)
This bachelor thesis deals with applications of Monte Carlo methods on various problems. In particular, Metropolis algorithm and Simulated Annealing were applied on optimization of Traveling Salesman Problem and the problem of graph coloring. Moreover, "traditional" Monte Carlo approach was utilized for statistical analysis of electronic circuits in which the values of components exhibit random variations with a given tolerance. The results are evaluated for different setups of Monte Carlo methods.
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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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