IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-1-4614-1701-9_8.html
   My bibliography  Save this book chapter

Primal-Dual Schema and Local Ratio

In: Design and Analysis of Approximation Algorithms

Author

Listed:
  • Ding-Zhu Du

    (University of Texas at Dallas)

  • Ker-I Ko

    (State University of New York at Stony Brook)

  • Xiaodong Hu

    (Academy of Mathematics and Systems Science Chinese Academy of Sciences)

Abstract

Based on the duality theory of linear programming, a new approximation technique, called the primal-dual schema, has been developed. With this technique, we do not need to compute the optimal solution of the relaxed linear program in order to get an approximate solution of the integer program. Thus, we can reduce the running time of many linear programming–based approximation algorithms from O(n3) to at most O(n2). Moreover, this method can actually be formulated in an equivalent form, called the local ratio method, which does not require the knowledge of the theory of linear programming. In this chapter, we study these two techniques and their relationship.

Suggested Citation

  • Ding-Zhu Du & Ker-I Ko & Xiaodong Hu, 2012. "Primal-Dual Schema and Local Ratio," Springer Optimization and Its Applications, in: Design and Analysis of Approximation Algorithms, chapter 8, pages 297-337, Springer.
    • Handle: RePEc:spr:spochp:978-1-4614-1701-9_8
    DOI: 10.1007/978-1-4614-1701-9_8
    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:spochp:978-1-4614-1701-9_8. 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.