  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.
