IDEAS home Printed from https://ideas.repec.org/a/ids/ijisen/v40y2022i3p309-324.html
   My bibliography  Save this article

Research on optimisation method for project site selection based on improved genetic algorithm

Author

Listed:
  • Ling-min Yang
  • Zhong-min Tang
  • Si-jun Liu

Abstract

In order to overcome the problems of low correlation between location impact index and target project, and low customer satisfaction in current research methods of project location, an optimisation method of project location based on improved genetic algorithm is proposed and designed. Collect the data needed for project site selection and integrate relevant data efficiently, and build the framework structure of project site selection. According to the evaluation index of project location, the existing genetic algorithm is improved. The improved genetic algorithm is applied to the optimisation of project location, and the eigenvalues and correlation factors of project location are optimised to realise the optimisation of project location. The experimental results show that the fit degree between the proposed method and the target project is between 0.9-1.0, and the user satisfaction is between 95%-99%, which proves that the proposed method has good robustness.

Suggested Citation

  • Ling-min Yang & Zhong-min Tang & Si-jun Liu, 2022. "Research on optimisation method for project site selection based on improved genetic algorithm," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 40(3), pages 309-324.
  • Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:309-324
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=122260
    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:ijisen:v:40:y:2022:i:3:p:309-324. 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=188 .

    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.