Research On Multiple Attribute Group Decision Making Approach And Its Applications In Supplier Selection

Supply chain management is one of the advanced management modes. The critical step in constructing of supply chain is partner selection. In the competition environment nowadays, supplier selection under SCM is more and more important. In order to enhance the accuracy and avoid making mistakes in such complex decision-making problems, important decisions in practice are normally taken by a group of people whose collective decision making ability is considered to be more credible than individual opinions. Therefore, the theories and methods of multiple attribute group decision-making show a wide prospect of applications in the field of supplier selection and the corresponding study is great significant.This thesis spreads out just based on the above background. The issue of multiple attribute group decision-making approach and its applications in supplier selection is studied further in this dissertation. And the research is made as follows:First, existing literatures on multiple attribute group decision making approach and its applications in supplier selection are outlined. And the limitations of them are analyzed. The structure and layout of this dissertation are described. Second, the thesis reviews the theories and methods of multiple attribute group decision-making systematically, especially, the methods of estimating the weights of experts and attributes. Third, on the background of SCM theory, the thesis analyses ordinary supplier selection process. And under the guide of the theory and method to establish indicator system, a supplier evaluation indicator system is developed based on the traditional supplier evaluation indicator system. Third, the thesis builds up a supplier evaluation modes based on group decision-making so as to study the problem about multiple attribute group decision-making approach's applications in supplier selection. The model uses a method of adjusting expert weight. That makes decision results more reasonable. Last, an instance is used to introduce the application of the model and calculation process given before in order to prove the feasibility and practicability of the model.