Fuzzy Environment, Vendor Selection Problem

With the rapid development of market economy, as "the third profit source", the logistics has drawn increasing attention, whose impact on economic activity is increasingly clear. The relationship between supply chain management and logistics activities are increasingly close, and supplier management is a very important question in the supply chain procurement, which plays a very important role to achieve JIT procurement, is an important part which connects with the consumers directly. Based on the research of domestic and foreign scholars on vendor selection, the concept of supply chain and supplier are introduced, the research status and development prospects of vendor selection are summarized, then a variety of vendor selection cases are further introduced. Considering a lot of information in reality is uncertain, problems relating to vendor selection under uncertain environment of the fuzzy environment are studied. The main works of the paper are as follows:Firstly, the vendor selection problem in which the shortage is not allowed under fuzzy environment is studied. Considering the suppliers' supply capacities and manufacturer's demands as fuzzy parameters, for the vendor selection problem about a single material supply and more supplies not allowed the shortage, this paper builds the corresponding fuzzy programming models, two solution methods are given. First of all, we solve them by using chance constrained method in fuzzy programming to transform the uncertain model into their equivalent formulation, next, we transform the fuzzy supplies and demands into mean area of fuzzy and design heuristic algorithms. At last, the two solution methods are compared using examples. Secondly, the vendor selection problem in which the shortage is allowed under fuzzy environment is studied. Considering the suppliers' supply capacities and manufacturer's demands as fuzzy parameters, For the vendor selection problem about a single material supply and more supplies allowed the shortage, this paper builds the corresponding fuzzy programming models, two solution methods are given, too. First of all, we solve them by using the interval-valued mean and the interval-valued possibilistic mean to transform the uncertain model into their equivalent formulation, next, we transform the fuzzy supplies and demands into mean area of fuzzy and design heuristic algorithms. At last, examples are given to compare the two solution methods and to confirm the feasibility and effectiveness of the algorithms.