Supply chain inventory strategies using fuzzy neural networks
H Wee, CE Wang, JC Chen, KJ Wang… - 9th Joint International …, 2006 - atlantis-press.com
H Wee, CE Wang, JC Chen, KJ Wang, YS Lin
9th Joint International Conference on Information Sciences (JCIS-06), 2006•atlantis-press.comIn 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 …
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 …
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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