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A New Framework for Metaheuristic Search Based on Animal Foraging

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Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 520))

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Abstract

In this paper, a new framework for metaheuristic search for global optimization is introduced. It is suitable for continuous nonlinear optimization problems. This framework is mimicking the seal pup behavior and its ability to search and choose the best lair to escape from predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy everytime consists of searching and selecting the best lair. For that, the seal pup performs a random walk to find a new lair. Stimulated by the sensitive nature of seals against external noise, the random walk is based on two search modes, normal mode and urgent mode. In normal mode, the pup moves between closely adjacent lairs via a Brownian walk. In urgent mode, the pup leaves the proximity area far away and performs a Levy walk to find a new lair from sparse targets. The switch between these two modes is realized by the random noise emitted by predators. The proposed framework can efficiently mimic seal pups behavior to find best location and provide a new approach to be used in global optimization problems.

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Acknowledgements

This work is supported by University of Malaya High Impact Research Grant no vote UM.C/625/HIR/MOHE/SC/13/2 from Ministry of Higher Education Malaysia.

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Authors and Affiliations

  1. Department of Information System, University of Malaya, Pantai Valley, 50603, Kuala Lumpur, Malaysia

    Younes Saadi, Edi Sutoyo, Mungad Mungad, Haruna Chiroma & Tutut Herawan

  2. Department of Information System, Universitas Ahmad Dahlan, Yogyakarta, Indonesia

    Iwan Tri Riyadi Yanto

Authors
  1. Younes Saadi
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  2. Iwan Tri Riyadi Yanto
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  3. Edi Sutoyo
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  4. Mungad Mungad
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  5. Haruna Chiroma
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  6. Tutut Herawan
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Corresponding author

Correspondence to Younes Saadi .

Editor information

Editors and Affiliations

  1. School of Information Technology, Deakin University, Geelong, VIC, Australia

    Jemal H. Abawajy

  2. Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia

    Mohamed Othman

  3. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Rozaida Ghazali

  4. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Mustafa Mat Deris

  5. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Hairulnizam Mahdin

  6. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

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Saadi, Y., Yanto, I.T.R., Sutoyo, E., Mungad, M., Chiroma, H., Herawan, T. (2019). A New Framework for Metaheuristic Search Based on Animal Foraging. In: Abawajy, J., Othman, M., Ghazali, R., Deris, M., Mahdin, H., Herawan, T. (eds) Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) . Lecture Notes in Electrical Engineering, vol 520. Springer, Singapore. https://doi.org/10.1007/978-981-13-1799-6_19

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