GRASP with Path-Relinking for Data Clustering: A Case Study for Biological Data

  • Rafael M. D. Frinhani
  • Ricardo M. A. Silva
  • Geraldo R. Mateus
  • Paola Festa
  • Mauricio G. C. Resende
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6630)


Cluster analysis has been applied to several domains with numerous applications. In this paper, we propose several GRASP with path-relinking heuristics for data clustering problems using as case study biological datasets. All these variants are based on the construction and local search procedures introduced by Nascimento et. al [22]. We hybridized the GRASP proposed by Nascimento et. al [22] with four alternatives for relinking method: forward, backward, mixed, and randomized. To our knowledge, GRASP with path-relinking has never been applied to cluster biological datasets. Extensive comparative experiments with other algorithms on a large set of test instances, according to different distance metrics (Euclidean, city block, cosine, and Pearson), show that the best of the proposed variants is both effective and efficient.


Local Search Scatter Search Local Search Procedure Annotate Bibliography Target Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rafael M. D. Frinhani
    • 1
  • Ricardo M. A. Silva
    • 2
    • 3
  • Geraldo R. Mateus
    • 1
  • Paola Festa
    • 4
  • Mauricio G. C. Resende
    • 5
  1. 1.Universidade Federal de Minas GeraisBelo HorizonteBrazil
  2. 2.Universidade Federal de LavrasLavrasBrazil
  3. 3.Universidade Federal de PernambucoRecifeBrazil
  4. 4.University of Napoli Federico IINapoliItaly
  5. 5.AT&T Labs ResearchFlorham ParkUSA

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