Solving Hierarchically Decomposable Problems with the Evolutionary Transition Algorithm

  • Tom Lenaerts
  • Anne Defaweux
Part of the Studies in Computational Intelligence book series (SCI, volume 250)


Capturing the metaphor of evolutionary transitions in biological complexity, the Evolutionary Transition Algorithm (ETA) evolves solutions of increasing structural and functional complexity from the symbiotic interaction of partial ones. From the definition it follows that this algorithm should be very well suited to solve hierarchically decomposable problems. In this chapter, we show that the ETA can indeed solve this kind of problems effectively.We analyze, in depth, its behavior on hierarchical problems of different size and modular complexity. These results are compared to the Symbiogenetic Model and it is shown that the ETA is more robust and efficient to tackle this kind of problems.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Tom Lenaerts
    • 1
  • Anne Defaweux
    • 2
  1. 1.MLG, Département d’InformatiqueUniversité Libre de BruxellesBrusselsBelgium
  2. 2.COMOVrije Universiteit BrusselBrusselsBelgium

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