The fuzzy logic is applied to resolve the monitoring problem of products quality and products quantity increasingly varying as market requirement. A series of fuzzy rules are employed and the fuzzy system may generate suggested supply change rate. At the same time, the operation of supplier is also dynamically changing and the evaluation and selection for supplier are the basis of supply –chain co-operation. So whether it is scientific to select a supplier is crucial for sustaining and developing a company. Therefore, in this paper the neural network is introduced to dynamically assess suppliers and recommend to substituting for new ones when necessary, only supplementing fuzzy logic system with its advantages. This paper describes the methodology for the deployment of this proposed hybrid approach to enhance the machine intelligence of a supply chain network with the description of a case study to exemplify its underlying principles.
Liu, Chunling; Meng, Bo; and Li, Jizi, "Monitoring the Supply of Products in a Supply Chain Environment: a Fuzzy Neural Approach" (2004). ICEB 2004 Proceedings (Beijing, China). 200.