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Geometric Particle Swarm Optimisation

  • Alberto Moraglio
  • Cecilia Di Chio
  • Riccardo Poli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4445)

Abstract

Using a geometric framework for the interpretation of crossover of recent introduction, we show an intimate connection between particle swarm optimization (PSO) and evolutionary algorithms. This connection enables us to generalize PSO to virtually any solution representation in a natural and straightforward way. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces.

Keywords

Particle Swarm Optimisation Search Space Equilibrium Point Convex Hull Genetic Program 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Alberto Moraglio
    • 1
  • Cecilia Di Chio
    • 1
  • Riccardo Poli
    • 1
  1. 1.Department of Computer Science, University of Essex, Wivenhoe Park, Colchester, CO4 3SQUK

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