A type-2 fuzzy system model for reducing bullwhip effects in supply chains and its application in steel manufacturing
作者： R. Gamasaee , M.H. Fazel Zarandi
DOI: 10.1016/J.SCIENT.2013.05.004
关键词: Fuzzy clustering 、 Bullwhip effect 、 Mathematical optimization 、 Computer science 、 Fuzzy control system 、 Fuzzy logic 、 Supply chain management 、 Demand forecasting 、 Fuzzy transportation 、 Bullwhip
摘要: Abstract The purpose of this paper is to evaluate and reduce the bullwhip effect in fuzzy environments by means type-2 methodology. In order a supply chain, we propose new method for demand forecasting. First, data real steel industry Canada clustered with an interval c -regression clustering algorithm. Then, novel hybrid expert system developed This uses Fuzzy Disjunctive Normal Forms (FDNF) Conjunctive (FCNF) aggregation antecedents. An policy determine orders chain. results proposed are compared type-1 as well time series literature. show that significantly reduced; also, has less error high accuracy.
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