IDEAS home Printed from https://ideas.repec.org/a/hin/complx/9054623.html
   My bibliography  Save this article

The Design of Contactors Based on the Niching Multiobjective Particle Swarm Optimization

Author

Listed:
  • Wenying Yang
  • Jiuwei Guo
  • Yang Liu
  • Guofu Zhai

Abstract

Contactors are important components in circuits. To solve the multiobjective optimization problems (MOPs) of contactors, a niching multiobjective particle swarm optimization (NMOPSO) with the entropy weight ideal point theory is proposed in this paper. The new algorithm selecting and archiving the nondominated solutions based on the niching theory to ensure the diversity of the nondominated solutions. To avoid missing the extreme solutions of each objective during the multiobjective optimization process, extra particle swarms used to search the independent optimal solution of each objective are supplemented in this algorithm. In order to determine the best compromise solution, a method to select the compromise solution based on entropy weight ideal point theory is also proposed in this paper. Using the algorithm to optimize the characteristics of a typical direct-acting contactor, the results show that the proposed algorithm can obtain the best compromise solution in MOPs.

Suggested Citation

  • Wenying Yang & Jiuwei Guo & Yang Liu & Guofu Zhai, 2018. "The Design of Contactors Based on the Niching Multiobjective Particle Swarm Optimization," Complexity, Hindawi, vol. 2018, pages 1-10, July.
    • Handle: RePEc:hin:complx:9054623
    DOI: 10.1155/2018/9054623
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/9054623.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/9054623.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/9054623?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

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


    Cited by:

    1. Fei Han & Yu-Wen-Tian Sun & Qing-Hua Ling, 2018. "An Improved Multiobjective Quantum-Behaved Particle Swarm Optimization Based on Double Search Strategy and Circular Transposon Mechanism," Complexity, Hindawi, vol. 2018, pages 1-22, November.

    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:hin:complx:9054623. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.