Salp swarm algorithm: a comprehensive survey

被引：306

作者：

Abualigah, Laith ^{[1
]}

Shehab, Mohammad ^{[2
]}

Alshinwan, Mohammad ^{[1
]}

Alabool, Hamzeh ^{[3
]}

机构：

[1] Amman Arab Univ, Fac Comp Sci & Informat, Amman, Jordan

[2] Aqaba Univ Technol, Dept Comp Sci, Aqaba, Jordan

[3] Saudi Elect Univ, Coll Comp & Informat, Abha, Saudi Arabia

来源：

NEURAL COMPUTING & APPLICATIONS | 2020年 / 32卷 / 15期

关键词：

Salp swarm algorithm; Meta-heuristic optimization algorithms; Optimization problems; Bio-inspired algorithms; KRILL HERD ALGORITHM; OPTIMIZATION ALGORITHM; PARAMETERS IDENTIFICATION; PV SYSTEMS; CONTROLLER; SEARCH; DESIGN;

D O I：

10.1007/s00521-019-04629-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：11195 / 11215

页数：21

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