A Novel Heuristic Memetic Clustering Algorithm
B.G.W. Craenen, A.K. Nandi, T. Ristaniemi

In this paper we introduce a novel clustering algorithm based on the Memetic
Algorithm meta-heuristic wherein clusters are iteratively evolved using a novel
single operator employing a combination of heuristics. Several heuristics are
described and employed for the three types of selections used in the operator.
The algorithm was exhaustively tested on three benchmark problems and compared
to a classical clustering algorithm (k-Medoids) using the same performance
metrics. The results show that our clustering algorithm consistently provides
better clustering solutions with less computational effort.