IDEAS home Printed from https://ideas.repec.org/a/ids/ijetma/v15y2012i3-4-5-6p305-324.html
   My bibliography  Save this article

A decision support system for waste collection management and its potential improvement with Radio-Frequency Identification Technology (RFID)

Author

Listed:
  • Izabela Nielsen
  • Ming K. Lim
  • Peter Nielsen
  • Rebecca Aggarwal

Abstract

Due to vigorous globalisation and product proliferation in recent years, more waste has been produced by the soaring manufacturing activities. This has contributed to the significant need for an efficient waste management system to ensure, with all efforts, the waste is properly treated for recycling or disposed. This paper presents a Decision Support System (DSS) framework, based on Constraint Logic Programming (CLP), for the collection management of industrial waste (of all kinds) and discusses the potential employment of Radio-Frequency Identification Technology (RFID) to improve several critical procedures involved in managing waste collection. This paper also demonstrates a widely distributed and semi-structured network of waste producing enterprises (e.g. manufacturers) and waste processing enterprises (i.e. waste recycling/treatment stations) improving their operations planning by means of using the proposed DSS. The potential RFID applications to update and validate information in a continuous manner to bring value-added benefits to the waste collection business are also presented.

Suggested Citation

  • Izabela Nielsen & Ming K. Lim & Peter Nielsen & Rebecca Aggarwal, 2012. "A decision support system for waste collection management and its potential improvement with Radio-Frequency Identification Technology (RFID)," International Journal of Environmental Technology and Management, Inderscience Enterprises Ltd, vol. 15(3/4/5/6), pages 305-324.
    • Handle: RePEc:ids:ijetma:v:15:y:2012:i:3/4/5/6:p:305-324
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=49230
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

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


    Cited by:

    1. M. Alimohammadi & J. Behnamian, 2024. "Investigating digital transformation technologically enabled solutions in reverse logistics: a systematic review," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 27137-27178, November.

    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:ids:ijetma:v:15:y:2012:i:3/4/5/6:p:305-324. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=11 .

    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.