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A new Multiobjective Artificial Bee Colony algorithm to solve a real-world frequency assignment problem
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Orientador(es)
Resumo(s)
Artificial bee colony (ABC) is a recently introduced algorithm that models the behavior of honey bee swarm to address a multiobjective version for ABC, named Multiobjective Artificial Bee Colony algorithm (MO-ABC). We describe the methodology and results obtained when applying the new MO-ABC metaheuristic, which was developed to solve a real-world frequency assignment problem (FAP) in GSM networks. A precise mathematical formulation for this problem was used, where the frequency plans are evaluated using accurate interference information taken from a real GSM network. In this paper, our work is divided into two stages: In the first one, we have accurately tuned the algorithm parameters. Then, in the second step, we have compared the MO-ABC with previous versions of distinct multiobjective algorithms already developed to the same instances of the problem. As we will see, results show that this approach is able to obtain reasonable frequency plans when solving a real-world FAP. In the results analysis, we consider as complementary metrics the hypervolume indicator to measure the quality of the solutions to this problem as well as the coverage relation information.
Descrição
Palavras-chave
Multiobjective optimization Frequency assignment problem MO-ABC real-world mobile network Metaheuristics
Contexto Educativo
Citação
da Silva Maximiano, M., Vega-Rodríguez, M.A., Gómez-Pulido, J.A. et al. A new Multiobjective Artificial Bee Colony algorithm to solve a real-world frequency assignment problem. Neural Comput & Applic 22, 1447–1459 (2013). https://doi.org/10.1007/s00521-012-1046-7
Editora
Springer Nature