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2004 | 14 | 3 | 317-333
Tytuł artykułu

Advances in parallel heterogeneous genetic algorithms for continuous optimization

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper we address an extension of a very efficient genetic algorithm (GA) known as Hy3, a physical parallelization of the gradual distributed real-coded GA (GD-RCGA). This search model relies on a set of eight subpopulations residing in a cube topology having two faces for promoting exploration and exploitation. The resulting technique has been shown to yield very accurate results in continuous optimization by using crossover operators tuned to explore and exploit the solutions inside each subpopulation. We introduce here a further extension of Hy3, called Hy4, that uses 16 islands arranged in a hypercube of four dimensions. Thus, two new faces with different exploration/exploitation search capabilities are added to the search performed by Hy3. We analyze the importance of running a synchronous versus an asynchronous version of the models considered. The results indicate that the proposed Hy4 model overcomes the Hy3 performance because of its improved balance between exploration and exploitation that enhances the search. Finally, we also show that the async Hy4 model scales better than the sync one.
Rocznik
Tom
14
Numer
3
Strony
317-333
Opis fizyczny
Daty
wydano
2004
otrzymano
2004-03-01
poprawiono
2004-06-01
Twórcy
autor
  • Dpto. de Lenguajes y Ciencias de la Computación, Universidad de Málaga. E.T.S.I. Informática Campus de Teatinos, Campus de Teatinos, 29071 Málaga, Spain
  • Dpto. de Lenguajes y Ciencias de la Computación, Universidad de Málaga. E.T.S.I. Informática Campus de Teatinos, Campus de Teatinos, 29071 Málaga, Spain
  • Dpto. de Lenguajes y Ciencias de la Computación, Universidad de Málaga. E.T.S.I. Informática Campus de Teatinos, Campus de Teatinos, 29071 Málaga, Spain
Bibliografia
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Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv14i3p317bwm
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