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A comprehensive survey on symbiotic organisms search algorithms

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Abstract

Recently, meta-heuristic algorithms have made remarkable progress in solving types of complex and NP-hard problems. So that, most of this algorithms are inspired by swarm intelligence and biological systems as well as other physical and chemical systems in nature. Of course, different divisions for meta-heuristic algorithms have been presented so far, and the number of these algorithms is increasing day by day. Among the meta-heuristic algorithms, some algorithms have a very high efficiency, which are a suitable method for solving real-world problems, but some algorithms have not been sufficiently studied. One of the nature-inspired meta-heuristic algorithms is symbiotic organisms search (SOS), which has been able to solve the majority of engineering issues so far. In this paper, firstly, the primary principles, the basic concepts, and mathematical relations of the SOS algorithm are presented and then the engineering applications of the SOS algorithm and published researches in different applications are examined as well as types of modified and multi-objective versions and hybridized discrete models of this algorithm are studied. This study encourages the researchers and developers of meta-heuristic algorithms to use this algorithm for solving various problems, because it is a simple and powerful algorithm to solve complex and NP-hard problems. In addition, a detailed and perfect statistical analysis was performed on the studies that had used this algorithm. According to the accomplished studies and investigations, features and factors of this algorithm are better than other meta-heuristic algorithm, which has increased its usability in various fields.

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Acknowledgements

Authors would like to thank the editor in chief, the associate editor, and reviewers for their constructive feedback during the review process. We deeply appreciate the reviewers’ comments for making this paper more complete.

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Authors and Affiliations

  1. Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran

    Farhad Soleimanian Gharehchopogh & Human Shayanfar

  2. Department of Computer Engineering and IT, Amirkabir University of Technology, Tehran, Iran

    Hojjat Gholizadeh

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  1. Farhad Soleimanian Gharehchopogh
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  2. Human Shayanfar
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  3. Hojjat Gholizadeh
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Correspondence to Farhad Soleimanian Gharehchopogh.

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Gharehchopogh, F.S., Shayanfar, H. & Gholizadeh, H. A comprehensive survey on symbiotic organisms search algorithms. Artif Intell Rev 53, 2265–2312 (2020). https://doi.org/10.1007/s10462-019-09733-4

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