Fuzzy knowledge-based token-ordering policies for bullwhip effect management in supply chains

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• 作者：M. H. Fazel Zarandi ; F. Shabany Moghadam
• 关键词：Supply chain management ; Bullwhip effect ; Fuzzy lead time ; Token ; based ordering policy ; Information sharing
• 刊名：Knowledge and Information Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：50
• 期：2
• 页码：607-631
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Information Systems and Communication Service; IT in Business;
• 出版者：Springer London
• ISSN：0219-3116
• 卷排序：50

文摘

The “Bullwhip Effect” is a well-known example of supply chain inefficiencies and refers to demand amplification as moving up toward upstream echelons in a supply chain. This paper concentrates on representing a robust token-based ordering policy to facilitate information sharing in supply chains in order to manage the bullwhip effect. Takagi–Sugeno–Kang and hybrid multiple-input single-output fuzzy models are proposed to model the mechanism of token ordering in the token-based ordering policy. The main advantage of proposed fuzzy models is that they eliminate the exogenous and constant variables from the procedure of obtaining the optimal amount of tokens which should be ordered in every period. These fuzzy approaches model the mentioned mechanism through a push–pull policy. A four-echelon SC with fuzzy lead time and unlimited production capacity and inventory is considered to survey the outcomes. Numerical experiments confirm the effectiveness of proposed policies in alleviating BWE, inventory costs and variations.