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Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms pp 139–155Cite as

Fish Inspired Algorithms

Part of the Intelligent Systems Reference Library book series (ISRL,volume 62)

Abstract

In this chapter, we present several fish algorithms that are inspired by some key features of the fish school/swarm, namely, artificial fish school algorithm (AFSA), fish school search (FSS), group escaping algorithm (GEA), and shark-search algorithm (SSA). We first provide a short introduction in Sect. 9.1. Then, the detailed descriptions regarding AFSA and FSS can be found in Sects. 9.2 and 9.3, respectively. Next, Sect. 9.4 briefs two emerging fish inspired algorithms, i.e., GEA and SSA. Finally, Sect. 9.5 summarises in this chapter

Keywords

  • Graphic Processing Unit
  • Steiner Tree
  • Individual Movement
  • Steiner Tree Problem
  • Fish School

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Authors and Affiliations

  1. Faculty of Engineering, Built Environment and Information Technology, Department of Mechanical Engineering and Aeronautical Engineering, University of Pretoria, Pretoria, South Africa

    Bo Xing

  2. Department of New Product Development, Meiyuan Mould Design and Manufacturing Co., Ltd., Xianghe, People’s Republic of China

    Wen-Jing Gao

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  1. Bo Xing
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  2. Wen-Jing Gao
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Correspondence to Bo Xing .

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Xing, B., Gao, WJ. (2014). Fish Inspired Algorithms. In: Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms. Intelligent Systems Reference Library, vol 62. Springer, Cham. https://doi.org/10.1007/978-3-319-03404-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-03404-1_9

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