IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i10p1647-d1658250.html
   My bibliography  Save this article

Memory-Based Differential Evolution Algorithms with Self-Adaptive Parameters for Optimization Problems

Author

Listed:
  • Shang-Kuan Chen

    (Department of Computer Science & Engineering, Yuan Ze University, Taoyuan 32003, Taiwan)

  • Gen-Han Wu

    (Department of Industrial Engineering & Engineering, Yuan Ze University, Taoyuan 32003, Taiwan)

  • Yu-Hsuan Wu

    (Department of Industrial Engineering & Engineering, Yuan Ze University, Taoyuan 32003, Taiwan)

Abstract

In this study, twelve modified differential evolution algorithms with memory properties and adaptive parameters were proposed to address optimization problems. In the experimental process, these modified differential evolution algorithms were applied to 23 continuous test functions. The results indicate that MBDE2 and IHDE-BPSO3 outperform the original differential evolution algorithm and its extended variants, consistently achieving optimal solutions in most cases. The findings suggest that the proposed improved differential evolution algorithm is highly adaptable across various problems, yielding superior results. Additionally, integrating memory properties significantly enhances the algorithm’s performance and effectiveness.

Suggested Citation

  • Shang-Kuan Chen & Gen-Han Wu & Yu-Hsuan Wu, 2025. "Memory-Based Differential Evolution Algorithms with Self-Adaptive Parameters for Optimization Problems," Mathematics, MDPI, vol. 13(10), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:10:p:1647-:d:1658250
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/10/1647/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/10/1647/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2025:i:10:p:1647-:d:1658250. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.