A multi-echelon inventory management framework for stochastic and fuzzy supply chains

被引：39

作者：

Gumus, Alev Taskin ^{[1
]}

Guneri, Ali Nat ^{[1
]}

机构：

[1] Yildiz Tech Univ, Dept Ind Engn, TR-34349 Besiktas, Turkey

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 03期

关键词：

Supply chain management; Multi-echelon inventory management; Stochastic cost model; Neural networks; Neuro-fuzzy approximation; OPTIMAL POLICIES; DEMAND UNCERTAINTY; SYSTEM; MODEL; APPROXIMATIONS; NETWORKS;

D O I：

10.1016/j.eswa.2008.06.082

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：5565 / 5575

页数：11

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