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Best-First Search Methods for Constrained Two-Dimensional Cutting Stock Problems

Author

Listed:
  • K. V. Viswanathan

    (Indian Institute of Management, Calcutta, India)

  • A. Bagchi

    (Indian Institute of Management, Calcutta, India and New Jersey Institute of Technology, Newark, New Jersey)

Abstract

Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle S of dimensions ( L , W ) is supplied. There are n types of demanded rectangles r 1 , r 2 , …, r n , with the i th type having length l i , width w i , value v i , and demand constraint b i . It is required to produce, from the stock rectangle S , a i copies of r i , 1 ≤ i ≤ n , to maximize a 1 v 1 + a 2 v 2 + · + a n v n subject to the constraints a i ≤ b i . Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods.

Suggested Citation

  • K. V. Viswanathan & A. Bagchi, 1993. "Best-First Search Methods for Constrained Two-Dimensional Cutting Stock Problems," Operations Research, INFORMS, vol. 41(4), pages 768-776, August.
    • Handle: RePEc:inm:oropre:v:41:y:1993:i:4:p:768-776
    DOI: 10.1287/opre.41.4.768
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    Citations

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    Cited by:

    1. Iori, Manuel & de Lima, Vinícius L. & Martello, Silvano & Miyazawa, Flávio K. & Monaci, Michele, 2021. "Exact solution techniques for two-dimensional cutting and packing," European Journal of Operational Research, Elsevier, vol. 289(2), pages 399-415.
    2. Mhand Hifi, 2004. "Dynamic Programming and Hill-Climbing Techniques for Constrained Two-Dimensional Cutting Stock Problems," Journal of Combinatorial Optimization, Springer, vol. 8(1), pages 65-84, March.
    3. Mhand Hifi & Catherine Roucairol, 2001. "Approximate and Exact Algorithms for Constrained (Un) Weighted Two-dimensional Two-staged Cutting Stock Problems," Journal of Combinatorial Optimization, Springer, vol. 5(4), pages 465-494, December.
    4. Russo, Mauro & Sforza, Antonio & Sterle, Claudio, 2013. "An improvement of the knapsack function based algorithm of Gilmore and Gomory for the unconstrained two-dimensional guillotine cutting problem," International Journal of Production Economics, Elsevier, vol. 145(2), pages 451-462.
    5. Hifi, Mhand, 1997. "The DH/KD algorithm: a hybrid approach for unconstrained two-dimensional cutting problems," European Journal of Operational Research, Elsevier, vol. 97(1), pages 41-52, February.
    6. Wu, Yu-Liang & Huang, Wenqi & Lau, Siu-chung & Wong, C. K. & Young, Gilbert H., 2002. "An effective quasi-human based heuristic for solving the rectangle packing problem," European Journal of Operational Research, Elsevier, vol. 141(2), pages 341-358, September.
    7. Krzysztof Fleszar, 2016. "An Exact Algorithm for the Two-Dimensional Stage-Unrestricted Guillotine Cutting/Packing Decision Problem," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 703-720, November.
    8. Lu, Hao-Chun & Huang, Yao-Huei, 2015. "An efficient genetic algorithm with a corner space algorithm for a cutting stock problem in the TFT-LCD industry," European Journal of Operational Research, Elsevier, vol. 246(1), pages 51-65.
    9. István Borgulya, 2019. "An EDA for the 2D knapsack problem with guillotine constraint," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(2), pages 329-356, June.
    10. Sławomir Bąk & Jacek Błażewicz & Grzegorz Pawlak & Maciej Płaza & Edmund K. Burke & Graham Kendall, 2011. "A Parallel Branch-and-Bound Approach to the Rectangular Guillotine Strip Cutting Problem," INFORMS Journal on Computing, INFORMS, vol. 23(1), pages 15-25, February.
    11. de Armas, Jesica & Miranda, Gara & León, Coromoto, 2012. "Improving the efficiency of a best-first bottom-up approach for the Constrained 2D Cutting Problem," European Journal of Operational Research, Elsevier, vol. 219(2), pages 201-213.
    12. Reinaldo Morabito & Vitória Pureza, 2010. "A heuristic approach based on dynamic programming and and/or-graph search for the constrained two-dimensional guillotine cutting problem," Annals of Operations Research, Springer, vol. 179(1), pages 297-315, September.
    13. Wei, Lijun & Lim, Andrew, 2015. "A bidirectional building approach for the 2D constrained guillotine knapsack packing problem," European Journal of Operational Research, Elsevier, vol. 242(1), pages 63-71.

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