IDEAS home Printed from https://ideas.repec.org/h/wsi/wschap/9789812819079_0005.html
   My bibliography  Save this book chapter

Parallel Local Search To Improve The Performance Of Genetic Algorithms

In: Challenges In Information Technology Management

Author

Listed:
  • YOUZHI ZHENG

    (Department of Computer Science and Technology, Tsinghua University, Beijing, China)

  • ZHENG QIN

    (Department of Computer Science and Technology, Tsinghua University, Beijing, China)

  • JUNLIANG CHEN

    (School of Software, Tsinghua University, Beijing, China)

Abstract

Genetic algorithms are promising search techniques dealing with the combinatorial optimization problems. The main disadvantage of GA is the slow convergence rate of the search. In order to improve convergence rate of the search, the former researchers put forward two common strategies, one is local search methods and the other is parallelization. This paper tries to combine the two strategies and design the architecture of parallel hybrid GA. We propose three parallel hybrid GAS: (1) GA holds the shared population, (2) local search holds the shared population, and (3) independent shared population. This paper selects message passing interface (MPI) to implement the parallel hybrid GAS program. We compare our parallel hybrid GA with the pure GA and the pipelining hybrid GA, and the results of the simulation show that parallel hybrid GAS can combine the merits of the local search approach and the parallel mechanism.

Suggested Citation

  • Youzhi Zheng & Zheng Qin & Junliang Chen, 2008. "Parallel Local Search To Improve The Performance Of Genetic Algorithms," World Scientific Book Chapters, in: Man-Chung Chan & Ronnie Cheung & James N K Liu (ed.), Challenges In Information Technology Management, chapter 5, pages 31-36, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812819079_0005
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/pdf/10.1142/9789812819079_0005
    Download Restriction: Ebook Access is available upon purchase.
    File URL: https://www.worldscientific.com/doi/abs/10.1142/9789812819079_0005
    Download Restriction: Ebook Access is available upon purchase.
    ---><---

    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:wsi:wschap:9789812819079_0005. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscientific.com/page/worldscibooks .

    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.