Enhanced Clustering Techniques for Hyper Network Planning Using Minimum Spanning Trees and Ant-Colony Algorithm
The goal of a clustering algorithm is to partition a given data set into clusters or groups, which are not predefined, such that the data points in a cluster are similar to each other more than points in different clusters. These groups are formed according to some measures of goodness that differ according to application. The field of "Ant algorithms" studies models derived from the observation of real ant's behavior and uses these models as a source of inspiration for the design of novel algorithms for solution of optimization and distributed control problems. Ant colony algorithms are a subset of swarm intelligence and consider the ability of simple ants to solve complex problems by cooperation.