IDEAS home Printed from https://ideas.repec.org/p/ebg/essewp/dr-05003.html
   My bibliography  Save this paper

Improved Approximation of the General Soft-Capacitated Facility Location Problem

Author

Listed:

Abstract

An NP-hard variant of the single-source Capacitated Facility Location Problem is studied, where each facility is composed of a variable number of fixed-capacity production units. This problem, especially the metric case, has been recently studied in several papers. In this paper, we only consider the general problem where connection costs do not systematically satisfy the triangle inequality property. We show that an adaptation of the set covering greedy heuristic, where the sub-problem is approximately solved by a Fully Polynomial-Time Approximation Scheme based on cost scaling and dynamic programming, achieves a logarithmic approximation ratio of (1+ƒÕ)H(n) for the problem, where n is the number of clients to be served, and H is the harmonic series. This improves the previous bound of 2H(n) for this problem.

Suggested Citation

  • Alfandari, Laurent, 2005. "Improved Approximation of the General Soft-Capacitated Facility Location Problem," ESSEC Working Papers DR 05003, ESSEC Research Center, ESSEC Business School.
  • Handle: RePEc:ebg:essewp:dr-05003
    as

    Download full text from publisher

    File URL: http://www.essec.fr/faculty/showDeclFileRes.do?declId=3996&key=__workpaper__
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Turken, Nazli & Carrillo, Janice & Verter, Vedat, 2017. "Facility location and capacity acquisition under carbon tax and emissions limits: To centralize or to decentralize?," International Journal of Production Economics, Elsevier, vol. 187(C), pages 126-141.

    More about this item

    Keywords

    Facility Location; Combinatorial optimization; Set Covering; Dynamic Programming; Approximation;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ebg:essewp:dr-05003. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sophie Magnanou). General contact details of provider: http://edirc.repec.org/data/essecfr.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.