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Scatter Search and Path Relinking: Advances and Applications

  • Fred Glover
  • Manuel Laguna
  • Rafael Marti
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 57)

Abstract

Scatter search (SS) is a population-based method that has recently been shown to yield promising outcomes for solving combinatorial and nonlinear optimization problems. Based on formulations originally proposed in the 1960s for combining decision rules and problem constraints, SS uses strategies for combining solution vectors that have proved effective in a variety of problem settings. Path relinking (PR) has been suggested as an approach to integrate intensification and diversification strategies in a search scheme. The approach may be viewed as an extreme (highly focused) instance of a strategy that seeks to incorporate attributes of high quality solutions, by creating inducements to favor these attributes in the moves selected. The goal of this paper is to examine SS and PR strategies that provide useful alternatives to more established search methods. We describe the features of SS and PR that set them apart from other evolutionary approaches, and that offer opportunities for creating increasingly more versatile and effective methods in the future. Specific applications are summarized to provide a clearer understanding of settings where the methods are being used.

Keywords

Local Search Tabu Search Scatter Search Maximum Clique Problem Graph Coloring Problem 
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

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Fred Glover
    • 1
  • Manuel Laguna
    • 1
  • Rafael Marti
    • 2
  1. 1.Leeds School of BusinessUniversity of ColoradoBoulderUSA
  2. 2.Dpto. de Estadística e Investigación Operativa, Facultad de MatemáticasUniversitat de ValenciaBurjassot, ValenciaSpain

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