9th Joint International Conference on Information Sciences (JCIS-06)

Supply chain inventory strategies using fuzzy neural networks

Authors
Hui Wee 0, C. Edward Wang, J. C. Chen, K.-J. Wang, Y.-S. Lin
Corresponding Author
Hui Wee
0Department of Industrial Engineering
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.285How to use a DOI?
Keywords
Fuzzy neural network, supply chain, inventory management
Abstract
In the fast-changing business environment, supply chains are affected by the production and inventory strategies, which influence the amount of information needed by the chains. The firms must therefore determine the best supply chain inventory strategies for their products. The lack of precise market demand and reliable supplier’s stock level makes it inappropriate to use the statistically-based inventory model to determine inventory strategies for the new product supply chain. This paper therefore presents a fuzzy neural network model to describe the uncertain market demand and supply reliability. By the joint replenishment and periodic review, we determine, under the consideration of long-term effect, the possible quantities of supply and customer’s demands in the multi-echelon acyclic network supply chain.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
DOI
https://doi.org/10.2991/jcis.2006.285How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Hui Wee
AU  - C. Edward Wang
AU  - J. C. Chen
AU  - K.-J. Wang
AU  - Y.-S. Lin
PY  - 2006/10
DA  - 2006/10
TI  - Supply chain inventory strategies using fuzzy neural networks
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/jcis.2006.285
DO  - https://doi.org/10.2991/jcis.2006.285
ID  - Wee2006/10
ER  -