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A new Multiobjective Artificial Bee Colony algorithm to solve a real-world frequency assignment problem

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Abstract

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.

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Acknowledgments

This work was partially funded by the Spanish Ministry of Science and Innovation and FEDER under the contract TIN2008-06491-C04-04 (the MSTAR project). Thanks also to the Polytechnic Institute of Leiria, for the economic support offered to Marisa Maximiano to make this research.

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Authors and Affiliations

  1. Department of Informatics Engineering. School of Technology and Management, Polytechnic Institute of Leiria, Campus 2—Morro do Lena—Alto do Vieiro, Apartado 4163, 2411-901, Leiria, Portugal

    Marisa da Silva Maximiano

  2. Department Technologies of Computers and Communications, University Extremadura, Escuela Politécnica, Campus Universitario s/n, 10003, Cáceres, Spain

    Miguel A. Vega-Rodríguez, Juan A. Gómez-Pulido & Juan M. Sánchez-Pérez

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  1. Marisa da Silva Maximiano
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  2. Miguel A. Vega-Rodríguez
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  3. Juan A. Gómez-Pulido
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  4. Juan M. Sánchez-Pérez
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Correspondence to Marisa da Silva Maximiano.

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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

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