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Resolution of strip-packing problems with genetic algorithms

Author

Listed:
  • A Gómez

    (University of Oviedo)

  • D de la Fuente

    (University of Oviedo)

Abstract

This paper studies strip-packing problems. It is our aim to optimise the position of a number of rectangular shapes on a base surface in order to minimise wastage of material. As the problem is a complex NP-complete one, a heuristic based on genetic algorithms (GA) is used to solve it. The main problem is the wide variety of genetic algorithms available in the literature, which makes it hard to know which variation is best suited to this type of problem. We conclude that using a cyclic crossover GA with fitness by area and variable mutation works best for this problem.

Suggested Citation

  • A Gómez & D de la Fuente, 2000. "Resolution of strip-packing problems with genetic algorithms," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(11), pages 1289-1295, November.
    • Handle: RePEc:pal:jorsoc:v:51:y:2000:i:11:d:10.1057_palgrave.jors.2601019
    DOI: 10.1057/palgrave.jors.2601019
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    Cited by:

    1. Hadjiconstantinou, Eleni & Iori, Manuel, 2007. "A hybrid genetic algorithm for the two-dimensional single large object placement problem," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1150-1166, December.
    2. Marco Antonio Boschetti & Lorenza Montaletti, 2010. "An Exact Algorithm for the Two-Dimensional Strip-Packing Problem," Operations Research, INFORMS, vol. 58(6), pages 1774-1791, December.

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