Partitional Algorithms for Hard Clustering Using Evolutionary and Swarm Intelligence Methods: A Survey.

Evolutionary and swarm intelligence methods attracted attention and gained popularity among the data mining researchers due to their expedient implementation, parallel nature, ability to search global optima and other advantages over conventional techniques. These methods along with their variants and hybrid approaches have emerged as worthwhile class of methods for clustering. Clustering is an unsupervised classification method. The partitional clustering algorithms look for hard clustering; they decompose the dataset into a set of disjoint clusters. This paper describes a brief review of evolutionary and swarm intelligence methods with their variants and hybrid approaches designed for partitional clustering algorithms for hard clustering of datasets.