Research Area: Metaheuristic Computing
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.
Keywords:
salp swarm algorithm
optimization problems
machine learning
engineering design
wireless networking
image processing
power energy
Author(s) Name: Laith Abualigah, Mohammad Shehab, Mohammad Alshinwan & Hamzeh Alabool
Journal name: Neural Computing and Applications
Conferrence name:
Publisher name: Springer
DOI: 10.1007/s00521-019-04629-4
Volume Information: 32, pages 11195–11215
