Open AccessA Survey on Cat Swarm Optimization Algorithm
Author(s) -
Rasheed Rebar Ihsan,
Saman M. Almufti,
Bijar M. S. Ormani,
Renas Rajab Asaad,
Ridwan Boya Marqas
Publication year - 2021
Publication title -
asian journal of research in computer science
Language(s) - English
Resource type - Journals
ISSN - 2581-8260
DOI - 10.9734/ajrcos/2021/v10i230237
Subject(s) - swarm behaviour , swarm intelligence , metaheuristic , computer science , multi swarm optimization , field (mathematics) , algorithm , mathematical optimization , optimization problem , optimization algorithm , particle swarm optimization , artificial intelligence , mathematics , pure mathematics
Swarm based optimization algorithms are a collection of intelligent techniques in the field of Artificial Intelligence (AI) were developed for simulating the intelligent behavior of animals. Over the years ago, problems complexity increased in a means that it is very difficult for basic mathematical approaches to obtain an optimum solution in an optimal time, this leads the researchers to develop various algorithms base on the natural behaviors of living beings for solving problems. This paper present a review for Cat Swarm Optimization (CSO), which is a powerful metaheuristic swarm-based optimization algorithm inspired by behaviors of cats in the Nature for solving optimization problems. Since its first appearances in 2006, CSO has been improved and applied in different fields by many researchers. In this review, we majorly focus on the original CSO algorithm and some improved branches of CSO family algorithms. Some examples of utilizing CSO to solve problems in engineering are also reviewed.