Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Collaborative supply chain planning using the artificial neural network approach

Collaborative supply chain planning using the artificial neural network approach The purpose of this paper is to show how the concepts of collaborative agents and artificial neural networks (ANNs) can work together to enable collaborative supply chain planning (SCP). An agent‐based supply chain network is decomposed into multiple ANNs in a way that the actual customer requirements and the agents' goals and constraints are matched in different stages. An error‐minimising algorithm which models the agents' collaboration mechanism is used to train three ANNs, namely the supply net, the production net and the delivery net, for pursuing complete order fulfilment across the supply chain. In the example problem, the collaborative SCP paradigm is applied to determine the supply plan of an alliance of small firms, which provides assemble‐to‐order goods with short delivery lead‐time to a regional market. The calculation results showed that the ANN approach achieved complete order fulfilment and significantly increased the resource utilisation of all supply chain agents. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Manufacturing Technology Management Emerald Publishing

Collaborative supply chain planning using the artificial neural network approach

Download PDF
10 pages

Loading next page...
 
/lp/emerald-publishing/collaborative-supply-chain-planning-using-the-artificial-neural-BQ32o0B80F

References (14)

Publisher
Emerald Publishing
Copyright
Copyright © 2004 Emerald Group Publishing Limited. All rights reserved.
ISSN
1741-038X
DOI
10.1108/17410380410565375
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to show how the concepts of collaborative agents and artificial neural networks (ANNs) can work together to enable collaborative supply chain planning (SCP). An agent‐based supply chain network is decomposed into multiple ANNs in a way that the actual customer requirements and the agents' goals and constraints are matched in different stages. An error‐minimising algorithm which models the agents' collaboration mechanism is used to train three ANNs, namely the supply net, the production net and the delivery net, for pursuing complete order fulfilment across the supply chain. In the example problem, the collaborative SCP paradigm is applied to determine the supply plan of an alliance of small firms, which provides assemble‐to‐order goods with short delivery lead‐time to a regional market. The calculation results showed that the ANN approach achieved complete order fulfilment and significantly increased the resource utilisation of all supply chain agents.

Journal

Journal of Manufacturing Technology Management – Emerald Publishing

Published: Dec 1, 2004

Keywords: Supply chain management; Neural nets; Manufacturing resource planning

There are no references for this article.