Abstract
This paper presents an in-depth survey and performance evaluation of the
Cat Swarm Optimization (CSO) Algorithm. CSO is a robust and powerful
metaheuristic swarm-based optimization approach that has received very
positive feedback since its emergence. It has been tackling many
optimization problems and many variants of it have been introduced.
However, the literature lacks a detailed survey or a performance
evaluation in this regard. Therefore, this paper is an attempt to review
all these works, including its developments and applications, and group
them accordingly. In addition, CSO is tested on 23 classical benchmark
functions and 10 modern benchmark functions (CEC 2019). The results are
then compared against three novel and powerful optimization algorithms,
namely Dragonfly algorithm (DA), Butterfly optimization algorithm (BOA)
and Fitness Dependent Optimizer (FDO). These algorithms are then ranked
according to Friedman test and the results show that CSO ranks first on
the whole. Finally, statistical approaches are employed to further
confirm the outperformance of CSO algorithm.