National Repository of Grey Literature 55 records found  beginprevious36 - 45next  jump to record: Search took 0.01 seconds. 
Implementation and Visualization of Classic Genetic Algorithm Using Metropolis Algorithm
Matula, Radek ; Jaroš, Jiří (referee) ; Ohlídal, Miloš (advisor)
This bachelor's thesis contains description of utilisation genetic and Metropolis algorithm to solution the Traveling Salesman Problem (TSP). Thesis describes process of development aplication POC and explains problems with adjusting parameters of algorithm.
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.
Traveling Salesman Problem - Serial Methods
Štys, Jiří ; Bidlo, Michal (referee) ; Kašpárek, Tomáš (advisor)
This bachelor's thesis describes some algorithm which solves traveling salesman problem by the help of serial methods. This thesis deals with efficiency analysis and scalability of this problem.
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.  
Solving of Optimisation Tasks Inspired by Living Organisms
Popek, Miloš ; Peringer, Petr (referee) ; Martinek, David (advisor)
We meet with solving of optimization problems every day, when we try to do our tasks in the best way. An Ant Colony Optimization is an algorithm inspired by behavior of ants seeking a source of food. The Ant Colony Optimization is successfuly using on optimization tasks, on which is not possible to use a classical optimization methods. A Genetic Algorithm is inspired by transmision of a genetic information during crossover. The Genetic Algorithm is used for solving optimization tasks like the ACO algorithm. The result of my master's thesis is created simulator for solving choosen optimization tasks by the ACO algorithm and the Genetic Algorithm and a comparison of gained results on implemented tasks.
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.
The Use of Means of Artificial Intelligence for the Decision Making Support in the Firm
Rosa, Štěpán ; Kříž, Jiří (referee) ; Dostál, Petr (advisor)
The diploma thesis focuses on the use of genetic algorithms for tasks related to the travelling salesman problem. Based on theoretical knowledge and problem analysis a proposal of the solution is provided. This creates a daily route plan for service technicians with regard to constraints. The case study shows that the proposed solution in comparison with manual scheduling by experience enables to reduce transportation costs.
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.
Computer service ‒ an aplication of traveling salesman problem
Ryglová, Michaela ; Skočdopolová, Veronika (advisor) ; Dvořák, Marek (referee)
The travelling salesman problem is one of the most popular kind of route trip transportation problem. This thesis deals with the solution of traveling salesman problem to minimize distance in kilometres and focus on customer requirements, I am using data from firm CTR s.r.o. In addition to the basic model are also used mathematical model with modification tasks, so it is a model with hard time windows and a model with soft time windows. A practical solution is used in an optimization modeling language in Lingo software. The optimum solution was found for the model the traveling salesman and its modifications. The longest route 40.2 kilometers provides modification with a soft time windows, but gives the most emphasis on customer requirements. The shortest route 24 km is found with using a model the traveling salesman problem, but not considered any customer requirements.
Customer delivery routes optimization using Google Maps API
Borovský, Marek ; Šlajchrt, Zbyněk (advisor) ; Ivánek, Jiří (referee)
The main goal of this work is to implement a system, which will be able to optimize routes between warehouses and selected customers and visualize them using maps by the Google Inc. This problem is being analyzed not only on the theoretical, but also, and mainly, on the practical aspects and tries to find a gap in the market with similar applications.

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