Title of article :
A multi-echelon inventory management framework for stochastic and fuzzy supply chains
Author/Authors :
Gumus، نويسنده , , Alev Taskin and Guneri، نويسنده , , Ali Fuat، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
11
From page :
5565
To page :
5575
Abstract :
In this paper, for effective multi-echelon supply chains under stochastic and fuzzy environments, an inventory management framework and deterministic/stochastic-neuro-fuzzy cost models within the context of this framework are structured. Then, a numerical application in a three-echelon tree-structure chain is presented to show the applicability and performance of proposed framework. It can be said that, by our framework, efficient forecast data is ensured, realistic cost titles are considered in proposed models, and also the minimum total supply chain cost values under demand, lead time and expediting cost pattern changes are presented and examined in detail.
Keywords :
Neuro-fuzzy approximation , Stochastic cost model , Supply chain management , NEURAL NETWORKS , Multi-echelon inventory management
Journal title :
Expert Systems with Applications
Serial Year :
2009
Journal title :
Expert Systems with Applications
Record number :
2346020
Link To Document :
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