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title:
 
Supply chain inventory strategies using fuzzy neural networks
publication:
 
JCIS-2006 Proceedings
part of series:
  Advances in Intelligent Systems Research
ISBN:
  978-90-78677-01-7
ISSN:
  1951-6851
DOI:
  doi:10.2991/jcis.2006.285 (how to use a DOI)
author(s):
 
Hui Wee, C. Edward Wang, J. C. Chen, K.-J. Wang, Y.-S. Lin
corresponding author:
 
Hui Wee
publication date:
 
October 2006
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.
copyright:
 
© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
full text: