National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Aplikace mravenčích algoritmů
Olszar, Patrik ; Sedlák, David (referee) ; Bidlo, Michal (advisor)
This bachelor’s thesis focuses on the implementation and optimization of the ant colony algorithm in C++ for solving the traveling salesman problem (TSP) involving tens of thousands to hundreds of thousands of cities. Due to the high memory demands of traditional ant colony algorithms, which have a exponential expansion of the pheromone matrix, a restricted pheromone matrix was implemented. This technique effectively limits the memory size needed for the pheromone matrix and thus enhances the scalability of the algorithm. Additionally, the work uses techniques such as MAX–MIN, ant parallelization, dynamic adjustment of alpha and beta parameters, a nearest neighbor list, and VCSS. The results achieved a final path that is within 3.5-5% of the optimal solution.
Robot path planning by means of ant algorithms
Pěnčík, Martin ; Krček, Petr (referee) ; Dvořák, Jiří (advisor)
This thesis deals with robot path planning. It contains an overview of general approaches for path planning and describes methods of swarm intelligence and their application for robot path planning. This paper also contains proposals of adjustments for ant algorithms and it presents experimental results of algorithm implementation.
Robot path planning by means of ant algorithms
Pěnčík, Martin ; Krček, Petr (referee) ; Dvořák, Jiří (advisor)
This thesis deals with robot path planning. It contains an overview of general approaches for path planning and describes methods of swarm intelligence and their application for robot path planning. This paper also contains proposals of adjustments for ant algorithms and it presents experimental results of algorithm implementation.

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