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Type-Based Genetic Algorithms

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Intelligent Distributed Computing XIII (IDC 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 868))

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Abstract

This paper introduces a novel type-based genetic algorithm and its applications to two well-known problems: N-queen problem and finding the global minimum of the Rosenbrock function. The algorithm offers a new approach to internal structure of individuals in population of genetic algorithms.

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References

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Author information

Authors and Affiliations

  1. Computer Science Department, University of Massachusetts Boston, Boston, MA, 02125, USA

    Roman Sizov & Dan A. Simovici

Authors
  1. Roman Sizov
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  2. Dan A. Simovici
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Corresponding author

Correspondence to Roman Sizov .

Editor information

Editors and Affiliations

  1. SPIIRAS, St. Petersburg, Russia

    Igor Kotenko

  2. University of Craiova, Craiova, Romania

    Costin Badica

  3. SPIIRAS, St. Petersburg, Russia

    Vasily Desnitsky

  4. LAAS - CNRS, Toulouse Cedex 4, France

    Didier El Baz

  5. University of Novi Sad, Novi Sad, Serbia

    Mirjana Ivanovic

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Sizov, R., Simovici, D.A. (2020). Type-Based Genetic Algorithms. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_19

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