• DocumentCode
    3300450
  • Title

    The Research of 3PLs Provider Selection Based on Rough Set and PSO

  • Author

    Zhang, Jie

  • Author_Institution
    Dept. of the Finance, Hebei Univ. of Eng., Handan, China
  • fYear
    2009
  • fDate
    11-12 July 2009
  • Firstpage
    165
  • Lastpage
    168
  • Abstract
    In this paper, according to the characteristics of the third-party logistics (3PLs) provider selection, we put forward a new method for third-party logistics provider selection. A new evaluation model with Rough set and particle swarm optimization(PSO) neural network is founded based on the comprehensive evaluation index system of 3PL provider selection environment, A neural network model to the problem is trained by particle swarm optimization technique, which is a new adaptive algorithm based on a social-psychological metaphor. Rough Set is introduced to reduce numbers of evaluation indicators, thus reducing the dimensions of the input space of neural network model, when treating the reduced data as the input space of neural network model, we find that both the convergence speed and the evaluation accuracy are enhanced in comparison with the traditional neural network model.
  • Keywords
    logistics; neural nets; outsourcing; particle swarm optimisation; rough set theory; PSO; comprehensive evaluation index system; particle swarm optimization neural network; rough set; third-party logistics provider selection; Companies; Conference management; Decision making; Engineering management; Financial management; Kernel; Logistics; Neural networks; Outsourcing; Particle swarm optimization; 3PLS; PSO; Rough Set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Services Science, Management and Engineering, 2009. SSME '09. IITA International Conference on
  • Conference_Location
    Zhangjiajie
  • Print_ISBN
    978-0-7695-3729-0
  • Type

    conf

  • DOI
    10.1109/SSME.2009.39
  • Filename
    5233322