IDEAS home Printed from https://ideas.repec.org/a/igg/jamc00/v1y2010i2p34-49.html
   My bibliography  Save this article

A Hybrid Genetic Algorithm for Optimization of Two-dimensional Cutting-Stock Problem

Author

Listed:
  • Ahmed Mellouli

    (University of Sfax, Tunisia)

  • Faouzi Masmoudi

    (University of Sfax, Tunisia)

  • Imed Kacem

    (University Paul Verlaine - Metz, LITA, France)

  • Mohamed Haddar

    (University of Sfax, Tunisia)

Abstract

In this paper, the authors present a hybrid genetic approach for the two-dimensional rectangular guillotine oriented cutting-stock problem. In this method, the genetic algorithm is used to select a set of cutting patterns while the linear programming model permits one to create the lengths to produce with each cutting pattern to fulfil the customer orders with minimal production cost. The effectiveness of the hybrid genetic approach has been evaluated through a set of instances which are both randomly generated and collected from the literature.

Suggested Citation

  • Ahmed Mellouli & Faouzi Masmoudi & Imed Kacem & Mohamed Haddar, 2010. "A Hybrid Genetic Algorithm for Optimization of Two-dimensional Cutting-Stock Problem," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 1(2), pages 34-49, April.
    • Handle: RePEc:igg:jamc00:v:1:y:2010:i:2:p:34-49
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jamc.2010040103
    Download Restriction: no
    ---><---

    More about this item

    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:igg:jamc00:v:1:y:2010:i:2:p:34-49. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.