IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v4y2010i4p107.html
   My bibliography  Save this article

An Adaptive Genetic Algorithm for 2D Packing Problem

Author

Listed:
  • Baochun Wang

Abstract

Rectangle packing problems solved belong to NP-Hard Problems. It is complex combination optimization in nature. This, an adaptive hybrid algorithm is proposed, in order to deal with optimization Algorithm limitations. In the end, the high efficiency of the layout optimization strategy and reasoned conclusions is verified by simulation results.

Suggested Citation

  • Baochun Wang, 2010. "An Adaptive Genetic Algorithm for 2D Packing Problem," Modern Applied Science, Canadian Center of Science and Education, vol. 4(4), pages 107-107, April.
  • Handle: RePEc:ibn:masjnl:v:4:y:2010:i:4:p:107
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/5657/4572
    Download Restriction: no

    File URL: https://ccsenet.org/journal/index.php/mas/article/view/5657
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hopper, E. & Turton, B. C. H., 2001. "An empirical investigation of meta-heuristic and heuristic algorithms for a 2D packing problem," European Journal of Operational Research, Elsevier, vol. 128(1), pages 34-57, January.
    Full references (including those not matched with items on IDEAS)

    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. Jean-François Côté & Manuel Iori, 2018. "The Meet-in-the-Middle Principle for Cutting and Packing Problems," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 646-661, November.
    2. 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.
    3. Jie Fang & Yunqing Rao & Xusheng Zhao & Bing Du, 2023. "A Hybrid Reinforcement Learning Algorithm for 2D Irregular Packing Problems," Mathematics, MDPI, vol. 11(2), pages 1-17, January.
    4. 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.
    5. 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.
    6. Liu, D.S. & Tan, K.C. & Huang, S.Y. & Goh, C.K. & Ho, W.K., 2008. "On solving multiobjective bin packing problems using evolutionary particle swarm optimization," European Journal of Operational Research, Elsevier, vol. 190(2), pages 357-382, October.
    7. Wenbin Zhu & Zhixing Luo & Andrew Lim & Wee-Chong Oon, 2016. "A fast implementation for the 2D/3D box placement problem," Computational Optimization and Applications, Springer, vol. 63(2), pages 585-612, March.
    8. Alvarez-Valdes, R. & Parreno, F. & Tamarit, J.M., 2007. "A tabu search algorithm for a two-dimensional non-guillotine cutting problem," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1167-1182, December.
    9. 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.
    10. Quadt, Daniel & Kuhn, Heinrich, 2007. "Batch scheduling of jobs with identical process times on flexible flow lines," International Journal of Production Economics, Elsevier, vol. 105(2), pages 385-401, February.
    11. Polyakovsky, Sergey & M'Hallah, Rym, 2009. "An agent-based approach to the two-dimensional guillotine bin packing problem," European Journal of Operational Research, Elsevier, vol. 192(3), pages 767-781, February.
    12. Wei, Lijun & Oon, Wee-Chong & Zhu, Wenbin & Lim, Andrew, 2011. "A skyline heuristic for the 2D rectangular packing and strip packing problems," European Journal of Operational Research, Elsevier, vol. 215(2), pages 337-346, December.
    13. Rosephine G. Rakotonirainy & Jan H. Vuuren, 2021. "The effect of benchmark data characteristics during empirical strip packing heuristic performance evaluation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(2), pages 467-495, June.
    14. 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.
    15. Alexander Hübner & Fabian Schäfer & Kai N. Schaal, 2020. "Maximizing Profit via Assortment and Shelf‐Space Optimization for Two‐Dimensional Shelves," Production and Operations Management, Production and Operations Management Society, vol. 29(3), pages 547-570, March.
    16. Allen, S.D. & Burke, E.K. & Kendall, G., 2011. "A hybrid placement strategy for the three-dimensional strip packing problem," European Journal of Operational Research, Elsevier, vol. 209(3), pages 219-227, March.
    17. E. K. Burke & G. Kendall & G. Whitwell, 2004. "A New Placement Heuristic for the Orthogonal Stock-Cutting Problem," Operations Research, INFORMS, vol. 52(4), pages 655-671, August.
    18. Imahori, S. & Yagiura, M. & Ibaraki, T., 2005. "Improved local search algorithms for the rectangle packing problem with general spatial costs," European Journal of Operational Research, Elsevier, vol. 167(1), pages 48-67, November.
    19. Wei, Lijun & Tian, Tian & Zhu, Wenbin & Lim, Andrew, 2014. "A block-based layer building approach for the 2D guillotine strip packing problem," European Journal of Operational Research, Elsevier, vol. 239(1), pages 58-69.
    20. 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.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    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:ibn:masjnl:v:4:y:2010:i:4:p:107. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.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.