Swarm Intelligence

, Volume 1, Issue 2, pp 95–113

Ant-based and swarm-based clustering

Article

DOI: 10.1007/s11721-007-0008-7

Cite this article as:
Handl, J. & Meyer, B. Swarm Intell (2007) 1: 95. doi:10.1007/s11721-007-0008-7

Abstract

Clustering with swarm-based algorithms is emerging as an alternative to more conventional clustering methods, such as hierarchical clustering and k-means. Ant-based clustering stands out as the most widely used group of swarm-based clustering algorithms. Broadly speaking, there are two main types of ant-based clustering: the first group of methods directly mimics the clustering behavior observed in real ant colonies. The second group is less directly inspired by nature: the clustering task is reformulated as an optimization task and general purpose ant-based optimization heuristics are utilized to find good or near-optimal clusterings. This papers reviews both approaches and places these methods in the wider context of general swarm-based clustering approaches.

Keywords

Ant-based clustering Swarm-based clustering Ant colony optimization Particle swarm optimization Clustering Data-mining 

Copyright information

© Springer Science + Business Media, LLC 2007

Authors and Affiliations

  1. 1.Manchester Interdisciplinary BiocentreUniversity of ManchesterManchesterUK
  2. 2.Clayton School of ITMonash UniversityMelbourneAustralia

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