Title :
The Research of 3PLs Provider Selection Based on Rough Set and PSO
Author_Institution :
Dept. of the Finance, Hebei Univ. of Eng., Handan, China
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;
Conference_Titel :
Services Science, Management and Engineering, 2009. SSME '09. IITA International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-0-7695-3729-0
DOI :
10.1109/SSME.2009.39