Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The “Bullwhip Effect” is a ll-known example of supply chain inefficiencies and refers to demand amplification as moving up toward upstream echelons in a supply chain.  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.
['M. H. Fazel Zarandi', 'F. Shabany Moghadam']
I am writing a research paper on a idea Fuzzy knowledge-based token-ordering policies for bullwhip effect management in supply chains
[{"from": "human", "value": "I am writing a research paper on a idea Fuzzy knowledge-based token-ordering policies for bullwhip effect management in supply chains"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The \u201cBullwhip Effect\u201d is a ll-known example of supply chain inefficiencies and refers to demand amplification as moving up toward upstream echelons in a supply chain.  concentrates on representing a robust token-based ordering policy to facilitate information sharing in supply chains in order to manage the bullwhip effect. Takagi\u2013Sugeno\u2013Kang 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\u2013pull 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."}]