IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-0-387-27744-8_13.html
   My bibliography  Save this book chapter

The Best-Fit Rule for Multibin Packing: An Extension of Graham's List Algorithms

In: Multidisciplinary Scheduling: Theory and Applications

Author

Listed:
  • Pierre Lemaire

    (Laboratoire Leibniz-IMAG)

  • Gerd Finke

    (Laboratoire Leibniz-IMAG)

  • Nadia Brauner

    (Laboratoire Leibniz-IMAG)

Abstract

In this paper, we deal with multibin packing problems. These problems are linked to multiprocessor-task scheduling as well as to bin packing problems: they consist of n objects to be packed into m bins, with each object requiring space in several bins. We propose an intuitive greedy approach (the best-fit rule), which extends the well-known list algorithms for multiprocessor scheduling, to solve the case when objects have fixed height and size. We prove that it provides a 2-approximation, and even a 4/3-approximation if the objects are sorted by non-increasing heights. Based on this method, a polynomial time approximation scheme (PTAS) will be developed.

Suggested Citation

  • Pierre Lemaire & Gerd Finke & Nadia Brauner, 2005. "The Best-Fit Rule for Multibin Packing: An Extension of Graham's List Algorithms," Springer Books, in: Graham Kendall & Edmund K. Burke & Sanja Petrovic & Michel Gendreau (ed.), Multidisciplinary Scheduling: Theory and Applications, pages 269-286, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-27744-8_13
    DOI: 10.1007/0-387-27744-7_13
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:sprchp:978-0-387-27744-8_13. 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: 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.