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Improving Artificial Fish Swarm Algorithm by Applying Group Escape Behavior of Fish

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Recent Advances in Soft Computing (ICSC-MENDEL 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 576))

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Abstract

Artificial fish swarm algorithm is a technique based on swarm behaviors that are inspired from schooling behaviors of fishes swarm in the nature. Group escaping is another interesting behavior of fish that is ignored. This behavior shows all fish change their moving directions rapidly while some fish sense a predator. In this paper, we proposed a new algorithm which is obtained by hybridizing artificial fish swarm algorithm and group escaping behavior of fish which can greatly speed up the convergence. It is presented proper pseudocode of improved algorithm and then experimental results on Traveling Salesman Problem is applied and demonstrated the advantages of the improved algorithm.

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Acknowledgements

The authors would like to thank the anonymous reviewers of this paper for their thought-provoking and insightful comments and corrections.

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Authors and Affiliations

  1. Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Seyed Hosein Iranmanesh, Fahimeh Tanhaie & Masoud Rabbani

  2. Research Institute for Energy Planning and Management (RIEMP), Tehran, Iran

    Seyed Hosein Iranmanesh

Authors
  1. Seyed Hosein Iranmanesh
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  2. Fahimeh Tanhaie
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  3. Masoud Rabbani
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Corresponding author

Correspondence to Seyed Hosein Iranmanesh .

Editor information

Editors and Affiliations

  1. Department of Applied Computer Science, Institute of Automation and Computer Science, Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic

    Radek Matoušek

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Iranmanesh, S.H., Tanhaie, F., Rabbani, M. (2017). Improving Artificial Fish Swarm Algorithm by Applying Group Escape Behavior of Fish. In: Matoušek, R. (eds) Recent Advances in Soft Computing. ICSC-MENDEL 2016. Advances in Intelligent Systems and Computing, vol 576. Springer, Cham. https://doi.org/10.1007/978-3-319-58088-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-58088-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58087-6

  • Online ISBN: 978-3-319-58088-3

  • eBook Packages: EngineeringEngineering (R0)

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