IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v07y2008i01ns0219622008002818.html
   My bibliography  Save this article

Improved Projection Hopfield Network For The Quadratic Assignment Problem

Author

Listed:
  • KEIJI TATSUMI

    (Division of Electrical, Electronic and Information Engineering, Graduate School of Engineering, Osaka University, Yamada-Oka 2-1, Suita, Osaka 565-0871, Japan)

  • TETSUZO TANINO

    (Division of Electrical, Electronic and Information Engineering, Graduate School of Engineering, Osaka University, Yamada-Oka 2-1, Suita, Osaka 565-0871, Japan)

Abstract

The continuous-valued Hopfield neural network (CHN) is a popular and powerful metaheuristic method for combinatorial optimization. However, it is difficult to select appropriate penalty parameters for constraints so as to obtain a feasible and desirable solution by CHN. Thus, various improved models have been proposed. Matsuda proposed a CHN named optimal CHN and showed theoretical results on selecting parameters. On the other hand, Smithet al.proposed the projection CHN which projects a solution onto the feasible region and thus needs not select penalty parameters.In this paper, we point out some drawbacks of these two models and propose a new CHN with an efficient projection technique for the quadratic assignment problem, which overcomes these drawbacks. Moreover, we show that the proposed model can always find a feasible solution and that it has the local convergence property. Finally, we verify advantages of the proposed model through some numerical experiments.

Suggested Citation

  • Keiji Tatsumi & Tetsuzo Tanino, 2008. "Improved Projection Hopfield Network For The Quadratic Assignment Problem," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 7(01), pages 53-70.
  • Handle: RePEc:wsi:ijitdm:v:07:y:2008:i:01:n:s0219622008002818
    DOI: 10.1142/S0219622008002818
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622008002818
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219622008002818?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:wsi:ijitdm:v:07:y:2008:i:01:n:s0219622008002818. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.