National Repository of Grey Literature 4 records found  Search took 0.00 seconds. 
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.
Evolutionary Optimization of Freight Transportation
Beránek, Michal ; Drahošová, Michaela (referee) ; Bidlo, Michal (advisor)
The following thesis deals with optimization of freight transport planning. The goal is to minimize expenses connected to transportation, which emerge from travelled distance. The expenses can be heavily reduced, if the routes are correctly planned, especially when there is a large number of customers to be served. This thesis focuses on solving the problem by using the evolutional algorithms, that are optimization methods based on principles of evolution. Thesis concentrates on Heterogeneous Fixed Fleet Vehicle Routing Problem. Thesis introduces multiple evolutional algorithms and their results are compared. The best algorithm, evolutional strategy with local neighbourhood search, achieves similar, for certain tasks even better results, than other existing evolutional algorithms, created to solve given problem.
Evolutionary Optimization of Freight Transportation
Beránek, Michal ; Drahošová, Michaela (referee) ; Bidlo, Michal (advisor)
The following thesis deals with optimization of freight transport planning. The goal is to minimize expenses connected to transportation, which emerge from travelled distance. The expenses can be heavily reduced, if the routes are correctly planned, especially when there is a large number of customers to be served. This thesis focuses on solving the problem by using the evolutional algorithms, that are optimization methods based on principles of evolution. Thesis concentrates on Heterogeneous Fixed Fleet Vehicle Routing Problem. Thesis introduces multiple evolutional algorithms and their results are compared. The best algorithm, evolutional strategy with local neighbourhood search, achieves similar, for certain tasks even better results, than other existing evolutional algorithms, created to solve given problem.
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.

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