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A parallel multi-population genetic algorithm for a constrained two-dimensional orthogonal packing problem

Author

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  • José Fernando Gonçalves

    (Faculdade de Economia do Porto)

  • Mauricio G. C. Resende

    (AT&T Labs Research)

Abstract

This paper addresses a constrained two-dimensional (2D), non-guillotine restricted, packing problem, where a fixed set of small rectangles has to be placed into a larger stock rectangle so as to maximize the value of the rectangles packed. The algorithm we propose hybridizes a novel placement procedure with a genetic algorithm based on random keys. We propose also a new fitness function to drive the optimization. The approach is tested on a set of instances taken from the literature and compared with other approaches. The experimental results validate the quality of the solutions and the effectiveness of the proposed algorithm.

Suggested Citation

  • José Fernando Gonçalves & Mauricio G. C. Resende, 2011. "A parallel multi-population genetic algorithm for a constrained two-dimensional orthogonal packing problem," Journal of Combinatorial Optimization, Springer, vol. 22(2), pages 180-201, August.
    • Handle: RePEc:spr:jcomop:v:22:y:2011:i:2:d:10.1007_s10878-009-9282-1
    DOI: 10.1007/s10878-009-9282-1
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    References listed on IDEAS

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