A Memetic Island Model for Discrete Tomography Reconstruction

  • Marco Cipolla
  • Giosuè Lo Bosco
  • Filippo Millonzi
  • Cesare Valenti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6857)

Abstract

Soft computing is a term indicating a coalition of methodologies, and its basic dogma is that, in general, better results can be obtained through the use of constituent methodologies in combination, rather than in a stand alone mode. Evolutionary computing belongs to this coalition, and thus memetic algorithms. Here, we present a combination of several instances of a recently proposed memetic algorithm for discrete tomography reconstruction, based on the island model parallel implementation. The combination is motivated by the fact that, even though the results of the recently proposed approach are finally better and more robust compared to other approaches, we advised that its major drawback was the computational time. The underlying combination strategy consists in separated populations of agents evolving by means of different processes which share some individuals, from time to time. Experiments were performed to test the benefits of this paradigm in terms of computational time and correctness of the solutions.

Keywords

Genetic Algorithm Memetic Algorithm Generic Image Island Model Discrete Tomography 
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 2011

Authors and Affiliations

  • Marco Cipolla
    • 1
  • Giosuè Lo Bosco
    • 1
  • Filippo Millonzi
    • 1
  • Cesare Valenti
    • 1
  1. 1.Dipartimento di Matematica e InformaticaUniversità di PalermoItaly

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