In recent years supplier selection and order allocation as an important part of supply chain management are facing unprecedented challenges and difficulties. High customization and fast changing market demands pressure the modern supply chain management. The problem is even more serious in Small to Medium Enterprises manufacturing (SMEs) networks. The problem of how to form and coordinate manufacturing networks effectively continues to form the basis of much research. A hybrid Fuzzy Analytical Hierarchy process (FAHP) and Genetic Algorithms (GA) approach is presented in this thesis to address the problem. This research is based on an industrial case study. Data and information of suppliers are collected from a company acting as a system integrator in SMEs manufacturing network. The weights of supplier in terms of both qualitative and quantitative criteria are identified. And then, as a result of GA optimization, optimum combinations of suppliers and their production tasks are determined corresponding to the requirement of orders and their own capabilities. The results show that the proposed method is capable of optimizing the configuration of manufacturing networks and provides visualized information for decision makers.