New Ideas in Applying Scatter Search to Multiobjective Optimization

  • Antonio J. Nebro
  • Francisco Luna
  • Enrique Alba
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3410)

Abstract

This paper elaborates on new ideas of a scatter search algorithm for solving multiobjective problems. Our approach adapts the well-known scatter search template for single objective optimization to the multiobjective field. The result is a simple and new metaheuristic called SSMO, which incorporates typical concepts from the multiobjective optimization domain such as Pareto dominance, crowding, and Pareto ranking. We evaluate SSMO with both constrained and unconstrained problems and compare it against NSGA-II. Preliminary results indicate that scatter search is a promising approach for multiobjective optimization.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Antonio J. Nebro
    • 1
  • Francisco Luna
    • 1
  • Enrique Alba
    • 1
  1. 1.Departamento de Lenguajes y Ciencias de la ComputaciónE.T.S. Ingeniería InformáticaMálagaSpain

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