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Salp swarm algorithm: a comprehensive survey

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Abstract

This paper completely introduces an exhaustive and a comprehensive review of the so-called salp swarm algorithm (SSA) and discussions its main characteristics. SSA is one of the efficient recent meta-heuristic optimization algorithms, where it has been successfully utilized in a wide range of optimization problems in different fields, such as machine learning, engineering design, wireless networking, image processing, and power energy. This review shows the available literature on SSA, including its variants, like binary, modifications and multi-objective. Followed by its applications, assessment and evaluation, and finally the conclusions, which focus on the current works on SSA, suggest possible future research directions.

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Authors and Affiliations

  1. Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan

    Laith Abualigah & Mohammad Alshinwan

  2. Department of Computer Science, Aqaba University of Technology, Aqaba, Jordan

    Mohammad Shehab

  3. College of Computing and Informatics, Saudi Electronic University, Abha, Saudi Arabia

    Hamzeh Alabool

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  1. Laith Abualigah
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  2. Mohammad Shehab
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  3. Mohammad Alshinwan
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Abualigah, L., Shehab, M., Alshinwan, M. et al. Salp swarm algorithm: a comprehensive survey. Neural Comput & Applic 32, 11195–11215 (2020). https://doi.org/10.1007/s00521-019-04629-4

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