Journal of Combinatorial Optimization

, Volume 31, Issue 1, pp 347–371 | Cite as

Efficient algorithms for cluster editing

  • Lucas Bastos
  • Luiz Satoru Ochi
  • Fábio Protti
  • Anand Subramanian
  • Ivan César Martins
  • Rian Gabriel S. Pinheiro
Article

Abstract

The cluster editing problem consists of transforming an input graph \(G\) into a cluster graph (a disjoint union of complete graphs) by performing a minimum number of edge editing operations. Each edge editing operation consists of either adding a new edge or removing an existing edge. In this paper we propose new theoretical results on data reduction and instance generation for the cluster editing problem, as well as two algorithms based on coupling an exact method to, respectively, a GRASP or ILS heuristic. Experimental results show that the proposed algorithms are able to find high-quality solutions in practical runtime.

Keywords

Combinatorial optimization Cluster editing Data reduction Metaheuristics Exact methods Hybrid algorithms 

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Lucas Bastos
    • 1
  • Luiz Satoru Ochi
    • 2
  • Fábio Protti
    • 2
  • Anand Subramanian
    • 3
  • Ivan César Martins
    • 2
  • Rian Gabriel S. Pinheiro
    • 2
  1. 1.Financiadora de Estudos e Projetos (FINEP)Praia do Flamengo 200 - 1ºandarRio de JaneiroBrazil
  2. 2.Universidade Federal FluminenseInstituto de ComputaçãoNiteróiBrazil
  3. 3.Universidade Federal da ParaíbaDepartamento de Engenharia de ProduçãoJoão PessoaBrazil

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