IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v121y2009i1p148-161.html
   My bibliography  Save this article

Active-set sequential quadratic programming method with compact neighbourhood algorithm for the multi-polygon mass production cutting-stock problem with rotatable polygons

Author

Listed:
  • Yu, M.T.
  • Lin, T.Y.
  • Hung, C.

Abstract

The cutting-stock problem, which considers how to arrange the component profiles on the material without overlaps, can increase the utility rate of the sheet stock, and is thus a standard constrained optimisation problem. In some applications the components should be placed with specific orientations, but in others the components may be placed with any orientation. This study presents an overlap index and it is much more suitable for the active-set SQP method which can reduce the time spend for constraint consideration. Using this method, various object orientations can be considered easily and the number of object on the sheet stock can be improved by up to eight percent.

Suggested Citation

  • Yu, M.T. & Lin, T.Y. & Hung, C., 2009. "Active-set sequential quadratic programming method with compact neighbourhood algorithm for the multi-polygon mass production cutting-stock problem with rotatable polygons," International Journal of Production Economics, Elsevier, vol. 121(1), pages 148-161, September.
    • Handle: RePEc:eee:proeco:v:121:y:2009:i:1:p:148-161
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925-5273(09)00151-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wascher, Gerhard & Hau[ss]ner, Heike & Schumann, Holger, 2007. "An improved typology of cutting and packing problems," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1109-1130, December.
    2. Jakobs, Stefan, 1996. "On genetic algorithms for the packing of polygons," European Journal of Operational Research, Elsevier, vol. 88(1), pages 165-181, January.
    3. Dowsland, Kathryn A. & Vaid, Subodh & Dowsland, William B., 2002. "An algorithm for polygon placement using a bottom-left strategy," European Journal of Operational Research, Elsevier, vol. 141(2), pages 371-381, September.
    4. Wong, W.K. & Leung, S.Y.S., 2008. "Genetic optimization of fabric utilization in apparel manufacturing," International Journal of Production Economics, Elsevier, vol. 114(1), pages 376-387, July.
    5. Gomes, A. Miguel & Oliveira, Jose F., 2002. "A 2-exchange heuristic for nesting problems," European Journal of Operational Research, Elsevier, vol. 141(2), pages 359-370, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. López-Camacho, Eunice & Terashima-Marín, Hugo & Ochoa, Gabriela & Conant-Pablos, Santiago Enrique, 2013. "Understanding the structure of bin packing problems through principal component analysis," International Journal of Production Economics, Elsevier, vol. 145(2), pages 488-499.
    2. Miguel Santoro & Felipe Lemos, 2015. "Irregular packing: MILP model based on a polygonal enclosure," Annals of Operations Research, Springer, vol. 235(1), pages 693-707, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J A Bennell & J F Oliveira, 2009. "A tutorial in irregular shape packing problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 93-105, May.
    2. Elkeran, Ahmed, 2013. "A new approach for sheet nesting problem using guided cuckoo search and pairwise clustering," European Journal of Operational Research, Elsevier, vol. 231(3), pages 757-769.
    3. Miguel Santoro & Felipe Lemos, 2015. "Irregular packing: MILP model based on a polygonal enclosure," Annals of Operations Research, Springer, vol. 235(1), pages 693-707, December.
    4. Lastra-Díaz, Juan J. & Ortuño, M. Teresa, 2024. "Mixed-integer programming models for irregular strip packing based on vertical slices and feasibility cuts," European Journal of Operational Research, Elsevier, vol. 313(1), pages 69-91.
    5. Eunice López-Camacho & Gabriela Ochoa & Hugo Terashima-Marín & Edmund Burke, 2013. "An effective heuristic for the two-dimensional irregular bin packing problem," Annals of Operations Research, Springer, vol. 206(1), pages 241-264, July.
    6. Umetani, Shunji & Murakami, Shohei, 2022. "Coordinate descent heuristics for the irregular strip packing problem of rasterized shapes," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1009-1026.
    7. Egeblad, Jens & Nielsen, Benny K. & Odgaard, Allan, 2007. "Fast neighborhood search for two- and three-dimensional nesting problems," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1249-1266, December.
    8. H. Terashima-Marín & P. Ross & C. Farías-Zárate & E. López-Camacho & M. Valenzuela-Rendón, 2010. "Generalized hyper-heuristics for solving 2D Regular and Irregular Packing Problems," Annals of Operations Research, Springer, vol. 179(1), pages 369-392, September.
    9. Chehrazad, Sahar & Roose, Dirk & Wauters, Tony, 2022. "A fast and scalable bottom-left-fill algorithm to solve nesting problems using a semi-discrete representation," European Journal of Operational Research, Elsevier, vol. 300(3), pages 809-826.
    10. 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.
    11. Igor Kierkosz & Maciej Luczak, 2014. "A hybrid evolutionary algorithm for the two-dimensional packing problem," 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. 22(4), pages 729-753, December.
    12. 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.
    13. Felix Prause & Kai Hoppmann-Baum & Boris Defourny & Thorsten Koch, 2021. "The maximum diversity assortment selection problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 93(3), pages 521-554, June.
    14. Igor Kierkosz & Maciej Łuczak, 2019. "A one-pass heuristic for nesting problems," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(1), pages 37-60.
    15. Germán Pantoja-Benavides & David Álvarez-Martínez & Francisco Parreño Torres, 2024. "The Normalized Direct Trigonometry Model for the Two-Dimensional Irregular Strip Packing Problem," Mathematics, MDPI, vol. 12(15), pages 1-25, August.
    16. Costa, M. Teresa & Gomes, A. Miguel & Oliveira, José F., 2009. "Heuristic approaches to large-scale periodic packing of irregular shapes on a rectangular sheet," European Journal of Operational Research, Elsevier, vol. 192(1), pages 29-40, January.
    17. 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.
    18. Nikolaus Furian & Siegfried Vössner, 2014. "A hybrid algorithm for constrained order packing," 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. 22(1), pages 157-186, March.
    19. Hinostroza, Ignacio & Pradenas, Lorena & Parada, Víctor, 2013. "Board cutting from logs: Optimal and heuristic approaches for the problem of packing rectangles in a circle," International Journal of Production Economics, Elsevier, vol. 145(2), pages 541-546.
    20. E. K. Burke & R. S. R. Hellier & G. Kendall & G. Whitwell, 2010. "Irregular Packing Using the Line and Arc No-Fit Polygon," Operations Research, INFORMS, vol. 58(4-part-1), pages 948-970, August.

    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:eee:proeco:v:121:y:2009:i:1:p:148-161. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.