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Solving the packing and strip-packing problems with genetic algorithms

  • Plasticity Phenomena (Maturing, Learning & Memory)
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Foundations and Tools for Neural Modeling (IWANN 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1606))

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Abstract

The aim of this article is to apply the methodology of genetic algorithms to the packing and Strip-packing problems. In both problems, the objective is the optimization of the position of a number of rectangular shapes on a base surface, in order to minimize the waste of material. Due to the difficulty of these problems, they are NP-Comptete problems, we use a heuristic to solve them, and in particular we use genetic algorithms. The main problem, is the great amount of type of genetic algorithms available in the literature, so that it is hard to know which variation is the best class of problems. Therefore, we use different types of genetic algorithms in order to obtain the best scheduling, and we compare the results obtained with the different approaches.

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Authors and Affiliations

  1. Dpto. de Administración de Empresas y Contabilidad, Universidad de Oviedo, Campus de Viesques, E-33271, Gijón, Spain

    Alberto Gomez & David de la Fuente

Authors
  1. Alberto Gomez
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  2. David de la Fuente
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José Mira Juan V. Sánchez-Andrés

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© 1999 Springer-Verlag Berlin Heidelberg

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Gomez, A., de la Fuente, D. (1999). Solving the packing and strip-packing problems with genetic algorithms. In: Mira, J., Sánchez-Andrés, J.V. (eds) Foundations and Tools for Neural Modeling. IWANN 1999. Lecture Notes in Computer Science, vol 1606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0098229

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  • DOI: https://doi.org/10.1007/BFb0098229

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66069-9

  • Online ISBN: 978-3-540-48771-5

  • eBook Packages: Springer Book Archive

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