Recent Versions and Applications of Sparrow Search Algorithm

被引:39
作者
Awadallah, Mohammed A. [1 ,2 ]
Al-Betar, Mohammed Azmi [3 ,4 ]
Doush, Iyad Abu [5 ,6 ]
Makhadmeh, Sharif Naser [3 ]
Al-Naymat, Ghazi [3 ]
机构
[1] Al Aqsa Univ, Dept Comp Sci, POB 4051, Gaza, Palestine
[2] Ajman Univ, Artificial Intelligence Res Ctr AIRC, Ajman, U Arab Emirates
[3] Ajman Univ, Coll Engn & Informat Technol, Artificial Intelligence Res Ctr AIRC, Ajman, U Arab Emirates
[4] Al Huson Univ Coll, Al Balqa Appl Univ, Dept Informat Technol, Irbid, Jordan
[5] Amer Univ Kuwait, Coll Engn & Appl Sci, Comp Dept, Salmiya, Kuwait
[6] Yarmouk Univ, Comp Sci Dept, Irbid, Jordan
关键词
NEURAL-NETWORK; OPTIMIZATION; PREDICTION; WIND;
D O I
10.1007/s11831-023-09887-z
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper reviews the latest versions and applications of sparrow search algorithm (SSA). It is a recent swarm-based algorithm proposed in 2020 rapidly grew due to its simple and optimistic features. SSA is inspired by the sparrow living style of foraging and the anti-predation behavior of sparrows. Since its establishment, it has been utilized for a plethora of optimization problems in different research topics, such as mechanical engineering, electrical engineering, civil engineering, power systems, industrial engineering, image processing, networking, environment, robotics, planing and scheduling, and healthcare. Initially, the growth of SSA and its theoretical features are highlighted in terms of the number of published articles, citations, topics covered, etc. After that, the different extended versions of SSA are reviewed, where the main variations of SSA are produced to avoid premature convergence and to boost the diversity aspects. These extended versions are modifications and hybridization summarized with more focus on the motivations behind establishing these versions. Multi-objective SSA is also presented as another version to deal with Multi-objective optimization problems. The critical analysis of the main research gaps in the convergence behaviour of SSA is discussed. Finally, the conclusion and the possible future expansions are recommended based on the research works accomplished in the literature.
引用
收藏
页码:2831 / 2858
页数:28
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