Model And Research For Bilevel Newsboy Problem In Fuzzy Environments

Newsboy model as an important application value and theoretical significance, it has been widely used in many industries and fields, newsboy problem and the extended model of attention by many scholars. For the supply chain Newsboy Problem, mostly around the central contralized supply chain. However, the current supply chain structure has been gradually changing from a centralized control for hierarchical control. Therefore, the use of bilevel decision model to describe systems suppliers and retailers system is more realistic, resulting in a bilevel newsboy problem. With the social development, product updates faster and faster, there are more and more Perishable Product and the season product. In many cases, the historical data is not reliable or not. So the stochastic demand model was restricted, fuzzy set theory gives a reasonable theoretical framework, and this uncertainty was called as fuzziness. Fuzzy set theory is applied to generate a fuzzy bilevel programming programming, applied to the bilevel newsboy of fuzzy bilevel programming problems have the bilevel newsboy problem under fuzzy environment, and this model can reflect the actual situation.Relevant fuzzy environment bilevel newsboy problem research mainly is aims at the market demand is ambiguous condition, but practice not only this kind of circumstance, with other fuzzy amount of bilevel newsboy problem of research is very little. This paper mainly on fuzzy constraint to the bilevel newsboy model is established, The bilevel newsboy problem in fuzzy environments is discussed, respectively established models of the constrain with fuzzy coefficient and the fuzzy constrain.The resolution of this problem is transformed mainly through the degree of satisfaction and the membership function. Then the bilevel newsboy problem is transformed into a general newsboy problem using K-T condition,Which suppliers can determine the appropriate wholesale price, order quantity of retailers to make the best buying decisions, making their final gain maximum benefit.