Advances in Sparrow Search Algorithm: A Comprehensive Survey

Archives of Computational Methods in Engineering - Tập 30 - Trang 427-455 - 2022
Farhad Soleimanian Gharehchopogh1, Mohammad Namazi2, Laya Ebrahimi1, Benyamin Abdollahzadeh1
1Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran
2Department of Computer Engineering, Maybod Branch, Islamic Azad University, Maybod, Iran

Tóm tắt

Mathematical programming and meta-heuristics are two types of optimization methods. Meta-heuristic algorithms can identify optimal/near-optimal solutions by mimicking natural behaviours or occurrences and provide benefits such as simplicity of execution, a few parameters, avoidance of local optimization, and flexibility. Many meta-heuristic algorithms have been introduced to solve optimization issues, each of which has advantages and disadvantages. Studies and research on presented meta-heuristic algorithms in prestigious journals showed they had good performance in solving hybrid, improved and mutated problems. This paper reviews the sparrow search algorithm (SSA), one of the new and robust algorithms for solving optimization problems. This paper covers all the SSA literature on variants, improvement, hybridization, and optimization. According to studies, the use of SSA in the mentioned areas has been equal to 32%, 36%, 4%, and 28%, respectively. The highest percentage belongs to Improved, which has been analyzed by three subsections: Meat-Heuristics, artificial neural networks, and Deep Learning.

Tài liệu tham khảo

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