DocumentCode
518377
Title
Notice of Retraction
Application of BP neural network and DEA in the logistics supplier selection
Author
Cheng-dong Shi ; Dun-xin Bian ; Su-ling Li
Author_Institution
Sch. of Electr. & Electron. Eng., Shandong Univ. of Technol., Zibo, China
Volume
1
fYear
2010
fDate
16-18 April 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In order to select appropriate logistics suppliers with BP neural network, a logistics supplier selection model was established based on artificial intelligence (BP neural network) and C2R-DEA (Data Envelopment Analysis). In the model, the C2R-DEA cross-evaluation method was introduced in detail, and the expected values of training samples (decision-making unit) were determined by the C2R-DEA cross-evaluation method. For illustration, an example was utilized to show the feasibility of the model in solving logistics supplier selection problem with twenty two listed logistics suppliers´ data in 2006. The example results show that the model can be able to identify the evaluation rank of alternative logistics suppliers and choose appropriate logistics supplier.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In order to select appropriate logistics suppliers with BP neural network, a logistics supplier selection model was established based on artificial intelligence (BP neural network) and C2R-DEA (Data Envelopment Analysis). In the model, the C2R-DEA cross-evaluation method was introduced in detail, and the expected values of training samples (decision-making unit) were determined by the C2R-DEA cross-evaluation method. For illustration, an example was utilized to show the feasibility of the model in solving logistics supplier selection problem with twenty two listed logistics suppliers´ data in 2006. The example results show that the model can be able to identify the evaluation rank of alternative logistics suppliers and choose appropriate logistics supplier.
Keywords
artificial intelligence; backpropagation; data envelopment analysis; decision making; logistics; neural nets; BP neural network application; DEA; artificial intelligence; data envelopment analysis; decision making unit; logistics supplier selection; Appropriate technology; Companies; Consumer electronics; Data engineering; Data envelopment analysis; Feedforward neural networks; Logistics; Multi-layer neural network; Neural networks; Outsourcing; BP neural network; DEA crossing-evaluation; logistics providers; selection model;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5486103
Filename
5486103
Link To Document