Heuristic Approaches for the Quartet Method of Hierarchical Clustering

Sergio Consoli*, Kenneth Darby-Dowman, Gijs Geleijnse, Jan Korst, Steffen Pauws

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)

Abstract

Given a set of objects and their pairwise distances, we wish to determine a visual representation of the data. We use the quartet paradigm to compute a hierarchy of clusters of the objects. The method is based on an NP-hard graph optimization problem called the Minimum Quartet Tree Cost problem. This paper presents and compares several heuristic approaches to approximate the optimal hierarchy. The performance of the algorithms is tested through extensive computational experiments and it is shown that the Reduced Variable Neighborhood Search heuristic is the most effective approach to the problem, obtaining high-quality solutions in short computational running times.

Original languageEnglish
Pages (from-to)1428-1443
Number of pages16
JournalIEEE Transactions on Knowledge and Data Engineering
Volume22
Issue number10
DOIs
Publication statusPublished - Oct 2010
Externally publishedYes

Keywords

  • Clustering
  • heuristic methods
  • optimization
  • graphs and networks
  • EVOLUTIONARY TREES
  • PHYLOGENIES
  • TOPOLOGIES

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