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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jie Zhang |
| Copyright Year | 2009 |
| 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. |
| Starting Page | 165 |
| Ending Page | 168 |
| File Size | 456693 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769537290 |
| DOI | 10.1109/SSME.2009.39 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-11 |
| Publisher Place | 09PR3729 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decision making Companies Conference management Financial management Rough Set Particle swarm optimization PSO Engineering management Neural networks Outsourcing 3PLS Kernel Logistics |
| Content Type | Text |
| Resource Type | Article |
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