IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v58y2014i4p769-794.html
   My bibliography  Save this article

Memetic algorithms and hyperheuristics applied to a multiobjectivised two-dimensional packing problem

Author

Listed:
  • Eduardo Segredo
  • Carlos Segura
  • Coromoto León

Abstract

Packing problems are np-hard problems with several practical applications. A variant of a 2d Packing Problem (2 dpp) was proposed in the gecco 2008 competition session. In this paper, Memetic Algorithms ( mas) and Hyperheuristics are applied to a multiobjectivised version of the 2 dpp. Multiobjectivisation is the reformulation of a mono-objective problem into a multi-objective one. The main aim of multiobjectivising the 2 dpp is to avoid stagnation in local optima. First generation mas refers to hybrid algorithms that combine a population-based global search with an individual learning process. A novel first generation ma is proposed, and an original multiobjectivisation method is applied to the 2 dpp. In addition, with the aim of facilitating the application of such first generation mas from the point of view of the parameter setting, and of enabling their usage in parallel environments, a parallel hyperheuristic is also applied. Particularly, the method applied here is a hybrid approach which combines a parallel island-based model and a hyperheuristic. The main objective of this work is twofold. Firstly, to analyse the advantages and drawbacks of a set of first generation mas. Secondly, to attempt to avoid those drawbacks by applying a parallel hyperheuristic. Moreover, robustness and scalability analyses of the parallel scheme are included. Finally, we should note that our methods improve on the current best-known solutions for the tested instances of the 2 dpp. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Eduardo Segredo & Carlos Segura & Coromoto León, 2014. "Memetic algorithms and hyperheuristics applied to a multiobjectivised two-dimensional packing problem," Journal of Global Optimization, Springer, vol. 58(4), pages 769-794, April.
    • Handle: RePEc:spr:jglopt:v:58:y:2014:i:4:p:769-794
    DOI: 10.1007/s10898-013-0088-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10898-013-0088-4
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10898-013-0088-4?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
    ---><---

    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. Lodi, Andrea & Martello, Silvano & Monaci, Michele, 2002. "Two-dimensional packing problems: A survey," European Journal of Operational Research, Elsevier, vol. 141(2), pages 241-252, September.
    3. Jaszkiewicz, Andrzej, 2002. "Genetic local search for multi-objective combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 137(1), pages 50-71, February.
    4. Silvano Martello & Michele Monaci & Daniele Vigo, 2003. "An Exact Approach to the Strip-Packing Problem," INFORMS Journal on Computing, INFORMS, vol. 15(3), pages 310-319, August.
    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. Gahm, Christian & Uzunoglu, Aykut & Wahl, Stefan & Ganschinietz, Chantal & Tuma, Axel, 2022. "Applying machine learning for the anticipation of complex nesting solutions in hierarchical production planning," European Journal of Operational Research, Elsevier, vol. 296(3), pages 819-836.
    2. Drake, John H. & Kheiri, Ahmed & Özcan, Ender & Burke, Edmund K., 2020. "Recent advances in selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 405-428.
    3. Carlos Segura & Carlos A. Coello Coello & Gara Miranda & Coromoto León, 2016. "Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization," Annals of Operations Research, Springer, vol. 240(1), pages 217-250, May.

    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. Francisco Trespalacios & Ignacio E. Grossmann, 2017. "Symmetry breaking for generalized disjunctive programming formulation of the strip packing problem," Annals of Operations Research, Springer, vol. 258(2), pages 747-759, November.
    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. Gardeyn, Jeroen & Wauters, Tony, 2022. "A goal-driven ruin and recreate heuristic for the 2D variable-sized bin packing problem with guillotine constraints," European Journal of Operational Research, Elsevier, vol. 301(2), pages 432-444.
    4. Ortmann, Frank G. & Ntene, Nthabiseng & van Vuuren, Jan H., 2010. "New and improved level heuristics for the rectangular strip packing and variable-sized bin packing problems," European Journal of Operational Research, Elsevier, vol. 203(2), pages 306-315, June.
    5. Leung, Stephen C.H. & Zhang, Defu & Sim, Kwang Mong, 2011. "A two-stage intelligent search algorithm for the two-dimensional strip packing problem," European Journal of Operational Research, Elsevier, vol. 215(1), pages 57-69, November.
    6. Önder Aşık & Ender Özcan, 2009. "Bidirectional best-fit heuristic for orthogonal rectangular strip packing," Annals of Operations Research, Springer, vol. 172(1), pages 405-427, November.
    7. Defu Zhang & Yuxin Che & Furong Ye & Yain-Whar Si & Stephen C. H. Leung, 2016. "A hybrid algorithm based on variable neighbourhood for the strip packing problem," Journal of Combinatorial Optimization, Springer, vol. 32(2), pages 513-530, August.
    8. Defu Zhang & Lijun Wei & Stephen C. H. Leung & Qingshan Chen, 2013. "A Binary Search Heuristic Algorithm Based on Randomized Local Search for the Rectangular Strip-Packing Problem," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 332-345, May.
    9. 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.
    10. Kenmochi, Mitsutoshi & Imamichi, Takashi & Nonobe, Koji & Yagiura, Mutsunori & Nagamochi, Hiroshi, 2009. "Exact algorithms for the two-dimensional strip packing problem with and without rotations," European Journal of Operational Research, Elsevier, vol. 198(1), pages 73-83, October.
    11. Gahm, Christian & Uzunoglu, Aykut & Wahl, Stefan & Ganschinietz, Chantal & Tuma, Axel, 2022. "Applying machine learning for the anticipation of complex nesting solutions in hierarchical production planning," European Journal of Operational Research, Elsevier, vol. 296(3), pages 819-836.
    12. 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.
    13. Bayliss, Christopher & Currie, Christine S.M. & Bennell, Julia A. & Martinez-Sykora, Antonio, 2021. "Queue-constrained packing: A vehicle ferry case study," European Journal of Operational Research, Elsevier, vol. 289(2), pages 727-741.
    14. 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.
    15. 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.
    16. Silva, Elsa & Oliveira, José Fernando & Silveira, Tiago & Mundim, Leandro & Carravilla, Maria Antónia, 2023. "The Floating-Cuts model: a general and flexible mixed-integer programming model for non-guillotine and guillotine rectangular cutting problems," Omega, Elsevier, vol. 114(C).
    17. 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.
    18. 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.
    19. Furini, Fabio & Malaguti, Enrico & Medina Durán, Rosa & Persiani, Alfredo & Toth, Paolo, 2012. "A column generation heuristic for the two-dimensional two-staged guillotine cutting stock problem with multiple stock size," European Journal of Operational Research, Elsevier, vol. 218(1), pages 251-260.
    20. Stéphane Grandcolas & Cyril Pain-Barre, 2022. "A hybrid metaheuristic for the two-dimensional strip packing problem," Annals of Operations Research, Springer, vol. 309(1), pages 79-102, 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:spr:jglopt:v:58:y:2014:i:4:p:769-794. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.