IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v41y1993i4p768-776.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.41.4.768
    Download Restriction: no

    File URL: https://libkey.io/10.1287/opre.41.4.768?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:oropre:v:41:y:1993:i:4:p:768-776. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.