Chapter

Advances in Artificial Intelligence - IBERAMIA-SBIA 2006

Volume 4140 of the series Lecture Notes in Computer Science pp 218-227

Pattern Sequencing Problems by Clustering Search

  • Alexandre C. M. OliveiraAffiliated withCarnegie Mellon UniversityDepartamento de Informática, Universidade Federal do Maranhão – UFMA
  • , Luiz A. N. LorenaAffiliated withCarnegie Mellon UniversityLaboratório Associado de Computação e Matemática Aplicada, Instituto Nacional de Pesquisas Espaciais – INPE

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Abstract

Modern search methods for optimization consider hybrid search metaheuristics those employing general optimizers working together with a problem-specific local search procedure. The hybridism comes from the balancing of global and local search procedures. A challenge in such algorithms is to discover efficient strategies to cover all the search space, applying local search only in actually promising search areas. This paper proposes the Clustering Search (*CS): a generic way of combining search metaheuristics with clustering to detect promising search areas before applying local search procedures. The clustering process aims to gather similar information about the problem at hand into groups, maintaining a representative solution associated to this information. Two applications to combinatorial optimization are examined, showing the flexibility and competitiveness of the method.

Keywords

Hybrid search metaheuristic pattern sequencing problem Clustering search