Ebrahim Teimoury
Mohammad Reza Gholamian
Bizhan Masoum
Mojgan Ghanavati

Clustering is a technique to categorize objects in k groups so that objects with most similar attribute values are placed in one group. Partitioning algorithms are a group of clustering algorithms and k-means algorithm is one of the most popular algorithms in this group that is very simple and fast but has some drawbacks too. In this paper we tried to propose an optimized hybrid clustering algorithm based on Honey Bee Mating algorithm and K-means in order to resolve these drawbacks. Finally, the performance of this optimized algorithm has been evaluated and compared with some other meta-heuristic clustering algorithms

Clustering algorithm, Honey Bee Mating algorithm, K-means, Meta-heuristics