Cat Swarm Optimization for Clustering

Abstract

Cat Swarm Optimization (CSO) is one of the new heuristic optimization algorithm which based on swarm intelligence. Previous research shows that this algorithm has better performance compared to the other heuristic optimization algorithms: Particle Swarm Optimization (PSO) and weighted-PSO in the cases of function minimization. In this research a new CSO algorithm for clustering problem is proposed. The new CSO clustering algorithm was tested on four different datasets. The modification is made on the CSO formula to obtain better results. Then, the accuracy level of poposed algorith was compared to those of K-means and PSO clustering. The modification of CSO formula can improve the performance of CSO Clustering. The comparison indicates that CSO clustering can be considered as a sufficiently accurate clustering method