A Survey on Cat Swarm Optimization Algorithm
Rasheed R. Ihsan, Saman M. Almufti, Bijar M. S. Ormani, Renas R. Asaad, Ridwan B. Marqas
Asian Journal of Research in Computer Science · pp. 22–32 · Published 29 Jun 2021
10.9734/ajrcos/2021/v10i230237Abstract
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.
Cited by 34
Pei-Wei Tsai, Swinburne University of Technology, Australia, Xingsi Xue · Applied Computing and Intelligence · 2021
Laith Abualigah, Aya Abusaleem, Abiodun M. Ikotun · Metaheuristic Optimization Algorithms · 2024
Shayesteh Tabatabaei · 2023
Kirti Pandey, C. K. Jha · Algorithms for Intelligent Systems · 2023
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