IDEAS home Printed from https://ideas.repec.org/a/hin/complx/1386407.html
   My bibliography  Save this article

Research on the Effect of DPSO in Team Selection Optimization under the Background of Big Data

Author

Listed:
  • Qian Zhao
  • Lian-ying Zhang

Abstract

Team selection optimization is the foundation of enterprise strategy realization; it is of great significance for maximizing the effectiveness of organizational decision-making. Thus, the study of team selection/team foundation has been a hot topic for a long time. With the rapid development of information technology, big data has become one of the significant technical means and played a key role in many researches. It is a frontier of team selection study by the means of combining big data with team selection, which has the great practical significance. Taking strategic equilibrium matching and dynamic gain as association constraints and maximizing revenue as the optimization goal, the Hadoop enterprise information management platform is constructed to discover the external environment, organizational culture, and strategic objectives of the enterprise and to discover the potential of the customer. And in order to promote the renewal of production and cooperation mode, a team selection optimization model based on DPSO is built. The simulation experiment method is used to qualitatively analyze the main parameters of the particle swarm optimization in this paper. By comparing the iterative results of genetic algorithm, ordinary particle swarm algorithm, and discrete particle swarm algorithm, it is found that the DPSO algorithm is effective and preferred in the study of team selection with the background of big data.

Suggested Citation

  • Qian Zhao & Lian-ying Zhang, 2018. "Research on the Effect of DPSO in Team Selection Optimization under the Background of Big Data," Complexity, Hindawi, vol. 2018, pages 1-14, July.
    • Handle: RePEc:hin:complx:1386407
    DOI: 10.1155/2018/1386407
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/1386407.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/1386407.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/1386407?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
    ---><---

    References listed on IDEAS

    as
    1. Karafyllis, Iasson & Jiang, Zhong-Ping & Athanasiou, George, 2010. "Nash Equilibrium and Robust Stability in Dynamic Games: A Small-Gain Perspective," MPRA Paper 26890, University Library of Munich, Germany, revised 23 Sep 2010.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Bo Wang & Yanjing Li & Fei Yang & Xiaohua Xia, 2019. "A Competitive Swarm Optimizer-Based Technoeconomic Optimization with Appliance Scheduling in Domestic PV-Battery Hybrid Systems," Complexity, Hindawi, vol. 2019, pages 1-15, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ryoichi Nishimura & Shunsuke Hayashi & Masao Fukushima, 2012. "Semidefinite complementarity reformulation for robust Nash equilibrium problems with Euclidean uncertainty sets," Journal of Global Optimization, Springer, vol. 53(1), pages 107-120, May.

    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:1386407. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.