IDEAS home Printed from https://ideas.repec.org/a/igg/jamc00/v13y2022i1p1-12.html
   My bibliography  Save this article

Using a Single Extra Constraint to Linearize the Quadratic Assignment Problem

Author

Listed:
  • Elias Munapo

    (North West University, South Africa)

Abstract

The paper presents a new powerful technique to linearize the quadratic assignment problem. There are so many techniques available in literature that are used to linearize the quadratic assignment problem. In all these linear formulations both the number of variables and linear constraints significantly increase. The technique proposed in this paper has the strength that the number of linear constraints increases by only one after linearization process. The QAP has application in areas such as wring, hospital layout, dartboard design, typewriter keyboard design, production process and scheduling.

Suggested Citation

  • Elias Munapo, 2022. "Using a Single Extra Constraint to Linearize the Quadratic Assignment Problem," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 13(1), pages 1-12, January.
    • Handle: RePEc:igg:jamc00:v:13:y:2022:i:1:p:1-12
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAMC.298651
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Viswanath Nagarajan & Maxim Sviridenko, 2009. "On the Maximum Quadratic Assignment Problem," Mathematics of Operations Research, INFORMS, vol. 34(4), pages 859-868, November.
    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. Santosh N. Kabadi & Abraham P. Punnen, 2011. "An O ( n 4 ) Algorithm for the QAP Linearization Problem," Mathematics of Operations Research, INFORMS, vol. 36(4), pages 754-761, November.

    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:13:y:2022:i:1:p:1-12. 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: 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.