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International Conference: Beyond Databases, Architectures and Structures

International Conference: Beyond Databases, Architectures and Structures

BDAS 2015, BDAS 2016: Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery pp 545–557Cite as

A New MGlaber Approach as an Example of Novel Artificial Acari Optimization

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 613))

Abstract

The proposed MGlaber method is based on observation of the behavior of mites called Macrocheles glaber (Muller, 1860). It opens the series of optimization methods inspired by the behavior of mites, which we have given a common name: Artificial Acari Optimization. Acarologists observed three stages the ovoviviparity process consists of, i.e.: preoviposition behaviour, oviposition behaviour (which is followed by holding an egg below the gnathosoma) and hatching of the larva supported by the female. It seems that the ovoviviparity phenomenon in this species is favoured by two factors, i.e.: poor feeding and poor quality of substrate. Experimental tests on a genetic algorithm were carried out. The MGlaber method was worked into a genetic algorithm by replacing crossig and mutation methods. The obtained results indicate to significant increase in the algorithm convergence without side-effects in the form of stopping of evolution at local extremes. The experiment was carried out one hundred times on random starting populations. No significant deviations of the measured results were observed. The research demonstrated significant increase in the algorithm operation speed. Convergence of evolution has increased about ten times. It should be noted here that MGlaber method was not only or even not primarily created for genetic algorithms. The authors perceive large potential for its application in all optimization methods where the decision about further future of the solutions is taken as a result of the evaluation of the objective function value. Therefore the authors treat this paper as the beginning of a cycle on Artificial Acari Optimization, which will include a series of methods inspired by behaviour of different species of mites.

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Acknowledgements

The authors would like to thank those who have proved their goodwill and assistance during the research. We direct special thanks for inspiration and access to the lab to Tomasz Marquardt, Behavioral Research Laboratory, Department of Evolutionary Biology, Kazimierz Wielki University in Bydgoszcz.

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Authors and Affiliations

  1. AIRlab Artificial Intelligence and Robotics Laboratory, Institute of Technology, Casimir the Great University in Bydgoszcz, ul. Chodkiewicza 30, 85-064, Bydgoszcz, Poland

    Jacek M. Czerniak & Dawid Ewald

Authors
  1. Jacek M. Czerniak
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  2. Dawid Ewald
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Corresponding author

Correspondence to Jacek M. Czerniak .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

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Czerniak, J.M., Ewald, D. (2016). A New MGlaber Approach as an Example of Novel Artificial Acari Optimization. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_42

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  • DOI: https://doi.org/10.1007/978-3-319-34099-9_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34098-2

  • Online ISBN: 978-3-319-34099-9

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