Advances in Clustering Search

  • Tarcisio Souza Costa
  • Alexandre César Muniz de Oliveira
  • Luiz Antonio Nogueira Lorena
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 73)


The Clustering Search (*CS) has been proposed as a generic way of combining search metaheuristics with clustering to detect promising search areas before applying local search procedures. The clustering process may keep representative solutions associated to different search subspaces. Although, recent applications have reached success in combinatorial optimisation problems, nothing new has arisen concerning diversification issues when population metaheuristics, as evolutionary algorithms, are being employed. In this work, recent advances in the *CS are commented and new features are proposed, including, the possibility of keeping population diversified for more generations.


Search Area Variable Neighborhood Search Promising Area Continuous Optimisation Local Search Procedure 
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 2010

Authors and Affiliations

  • Tarcisio Souza Costa
    • 1
  • Alexandre César Muniz de Oliveira
    • 1
  • Luiz Antonio Nogueira Lorena
    • 2
  1. 1.Universidade Federal do MaranhãoSão LuísBrasil
  2. 2.Instituto Nacional de Pesquisas Espaciais 

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