IDEAS home Printed from https://ideas.repec.org/a/igg/jsir00/v4y2013i1p78-124.html
   My bibliography  Save this article

Computational Intelligence in Used Products Retrieval and Reproduction

Author

Listed:
  • Wen-Jing Gao

    (Department of Electrical and Electronic Engineering, University of Johannesburg, Johannesburg, South Africa)

  • Bo Xing

    (Department of Electrical and Electronic Engineering, University of Johannesburg, Johannesburg, South Africa)

  • Tshilidzi Marwala

    (Department of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa)

Abstract

Remanufacturing has become a superior option for product recovery management system. It mainly consists of three stages: retrieval, reproduction, and redistribution. So far, many different approaches have been followed in order to improve the efficiency of a remanufacturing process. However, as the complexity increases, the use of computational intelligence (CI) in those problems is becoming a unique tool of imperative value. In this paper, different CI methods, such as artificial neural network (ANN), ant colony optimization (ACO), biogeography-based optimization (BBO), cuckoo search (CS) and fuzzy logic (FL), are utilized to solve the problems involved in retrieval and reproduction stages for remanufacturing. The key issues in implementing the proposed approaches are discussed, and finally the applicability of the proposed methods are illustrated through different examples.

Suggested Citation

  • Wen-Jing Gao & Bo Xing & Tshilidzi Marwala, 2013. "Computational Intelligence in Used Products Retrieval and Reproduction," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 4(1), pages 78-124, January.
    • Handle: RePEc:igg:jsir00:v:4:y:2013:i:1:p:78-124
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jsir.2013010104
    Download Restriction: no
    ---><---

    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:jsir00:v:4:y:2013:i:1:p:78-124. 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: 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.