Notification:
We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Study to selection of suppliers approach based on approved BP artificial neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Na Liu ; Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding ; Jianchang Lu ; Lin Zhu

Supplier selection is one of the most critical decisions in a supply chain. While it can contribute to the supply good suppliers, supply chain's overall incorrect selection can drive the whole chain into disarray. The back-propagation algorithm(BP) is a well-known method of training a multilayer feed-forward artificial neural networks(FFANNS). Although the algorithm is successful, it has some disadvantages. Because of adopting the gradient method by BP neural network, the problems including slowly learning convergent velocity and easily converging to local minimum can not be avoided. In addition, the selection of learning factor and inertial factor affects the convergence of BP neural network, which are usually determined by experiences. Therefore the effective application of BP neural network is limited. In this paper a new method in BP algorithm to avoid local minimum was proposed by means of adding gradually training data and hidden units. In addition, the paper also proposed a new model of controllable feed-forward neural network for supplier selection.

Published in:

Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on  (Volume:2 )

Date of Conference:

12-15 Oct. 2008