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Natural Intelligence for Scheduling, Planning and Packing Problems pp 111–143Cite as

Solving Hierarchically Decomposable Problems with the Evolutionary Transition Algorithm

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 250))

Abstract

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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Author information

Authors and Affiliations

  1. MLG, Département d’Informatique, Université Libre de Bruxelles, Boulevard du Triomphe CP212, 1050, Brussels, Belgium

    Tom Lenaerts

  2. COMO, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium

    Anne Defaweux

Authors
  1. Tom Lenaerts
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  2. Anne Defaweux
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Editor information

Editors and Affiliations

  1. School of Computing & Design, Swinburne University of Technology (Sarawak Campus), Jalan Simpang Tiga, 93350, Kuching, Sarawak, Malaysia

    Raymond Chiong  & Sandeep Dhakal  & 

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Lenaerts, T., Defaweux, A. (2009). Solving Hierarchically Decomposable Problems with the Evolutionary Transition Algorithm. In: Chiong, R., Dhakal, S. (eds) Natural Intelligence for Scheduling, Planning and Packing Problems. Studies in Computational Intelligence, vol 250. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04039-9_5

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  • DOI: https://doi.org/10.1007/978-3-642-04039-9_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04038-2

  • Online ISBN: 978-3-642-04039-9

  • eBook Packages: EngineeringEngineering (R0)

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