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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Advanced Evolutionary Optimisation of TSP-Based Problems
 Hladyuk, Vadym ; Vašíček, Zdeněk (referee) ; Bidlo, Michal (advisor)
This paper solves the traveling salesman problem using an evolutionary algorithm, specifically a genetic algorithm. It is a hybrid of the genetic algorithm, using a local search algorithm and other enhancements that further improve the results obtained. The traveling salesman problem will be solved from 20 cities to 25,000 cities. In the experiments chapter, I have determined the best settings for all the parameters in the program and properly tested their appropriateness. In the next part of the experiments chapter, I found out the performance of the full version of the genetic algorithm and its variants. In the last section, I compared the evolution of fitness values of different variants of genetic algorithms and different variants of crossover operators, I also compared the time consumption. I suggested further possible improvements either to the local search algorithm or to another approach to solve the TSP.
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Travelling Salesman Problem
 Řezníček, Jan ; Zbořil, František (referee) ; Zbořil, František (advisor)
The work focuses on implementing algorithms that solve the Traveling Salesman Problem. It also includes a user interface with a map for importing locations. The main algorithms that are part of the work are ACO and an algorithm that I have devised and implemented. ACO optimization improves results, such as setting initial pheromone levels using the nearest neighbor algorithm. My algorithm works on the principle of gradually improving the path.
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