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Memetic and Opposition-Based Learning Genetic Algorithms for Sorting Unsigned Genomes by Translocations

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Advances in Nature and Biologically Inspired Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 419))

Abstract

A standard genetic algorithm (\(\mathcal{G\!A}_{{ \mathrm{S}}}\)) for sorting unsigned genomes by translocations is improved in two different manners: firstly, a memetic algorithm (\(\mathcal{G\!A}_{{ \mathrm{M}}}\)) is provided, which embeds a new stage of local search, based on the concept of mutation applied in only one gene; secondly, an opposition-based learning (\(\mathcal{G\!A}_{{ \mathrm{OBL}}}\)) mechanism is provided that explores the concept of internal opposition applied to a chromosome. Both approaches include a convergence control mechanism of the population using the Shannon entropy. For the experiments, both biological and synthetic genomes were used. The results showed that \(\mathcal{G\!A}_{{ \mathrm{M}}}\)outperforms both \(\mathcal{G\!A}_{{ \mathrm{S}}}\)and \(\mathcal{G\!A}_{{ \mathrm{OBL}}}\)as confirmed through statistical tests.

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Author information

Authors and Affiliations

  1. Departaments of Computer Science, Universidade de Brasília, Brasília, Brazil

    Lucas A. da Silveira, José L. Soncco-Álvarez & Mauricio Ayala-Rincón

  2. Departaments of Computer Science and Mathematics, Universidade de Brasília, Brasília, Brazil

    Mauricio Ayala-Rincón

  3. Department of Mathematics, Universidade de Goiás—Campus II, Goiás, Brazil

    Thaynara A. de Lima

Authors
  1. Lucas A. da Silveira
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  2. José L. Soncco-Álvarez
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  3. Thaynara A. de Lima
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  4. Mauricio Ayala-Rincón
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Corresponding author

Correspondence to José L. Soncco-Álvarez .

Editor information

Editors and Affiliations

  1. School of Mathematics, Statistics and CS, University of KwaZulu-Natal, Pietermaritzburg, South Africa

    Nelishia Pillay

  2. Sch of IT, Dept of CS, University of Pretoria, Pretoria, South Africa

    Andries P. Engelbrecht

  3. Sci N/w for Innova and Research Exc, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  4. Department of Computing Sciences,, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa

    Mathys C. du Plessis

  5. Faculty of Electrical Engineering and, Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Václav Snášel

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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da Silveira, L.A., Soncco-Álvarez, J.L., de Lima, T.A., Ayala-Rincón, M. (2016). Memetic and Opposition-Based Learning Genetic Algorithms for Sorting Unsigned Genomes by Translocations. In: Pillay, N., Engelbrecht, A., Abraham, A., du Plessis, M., Snášel, V., Muda, A. (eds) Advances in Nature and Biologically Inspired Computing. Advances in Intelligent Systems and Computing, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-319-27400-3_7

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  • DOI: https://doi.org/10.1007/978-3-319-27400-3_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27399-0

  • Online ISBN: 978-3-319-27400-3

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