IDEAS home Printed from https://ideas.repec.org/a/ids/ijmtma/v36y2022i2-3-4p154-167.html
   My bibliography  Save this article

Optimisation design of reverse logistics network based on hybrid genetic algorithm

Author

Listed:
  • Yan Sun

Abstract

Traditional enterprise reverse logistics network optimisation has problems of low sales profit and low asset income rate. A new hybrid genetic algorithm is proposed to optimise it. First, this paper determines the influencing factors of reverse logistics network optimisation. Then constructs an enterprise reverse logistics network model and designs the decomposition and coordination algorithm that divides this reverse network into small groups. Finally, it judges the optimisation scheme and solves the reverse logistics network model with the help of genetic algorithm to optimise. It can be seen from the comparison: through this method, the profit margin of sales and return on assets can reach 90%; it can enhance the operating profit of the enterprise.

Suggested Citation

  • Yan Sun, 2022. "Optimisation design of reverse logistics network based on hybrid genetic algorithm," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 36(2/3/4), pages 154-167.
    • Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:154-167
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=123661
    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.

    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:ijmtma:v:36:y:2022:i:2/3/4:p:154-167. 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=21 .

    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.