In manufacturing industry selection of right supplier (s) is one of the challenging activities. Supplier selection is the method of determining the appropriate suppliers to provide the right quality of products, at the right quantities, at the right price in the right time. During the last ten years based on the changes in the business sector, Multi-Criteria Decision Making (MCDM) has been one of the fastest growing areas. By choosing the best supplier, the companies can increase their productivity and also competitive advantage. In the earlier period, several methods have been proposed to solve the supplier selection problem, such as the linear weighting methods, the analytic network process, total cost approaches and mathematical programming techniques. Although the linear programming methods are simple, they are not accurate and more variations exist. So the latest multi-criteria decision making tools such as Analytical Hierarchy Process (AHP), Fuzzy Logic (FL) and Artificial Neural Network (ANN) are deeply studied. While selecting the best supplier, many criteria are involved. The criteria may be different for different approach. The decision makers always express their preferences on alternatives or on the attributes of supplier which can be used to help rank the supplier and choose the enviable one. In this article, application of fuzzy logic and AHP are discussed with case-studies and also presented the discussion about implementation of ANN for supplier selection.
Optimization of Multi-Criteria Decision Making Analysis for Selection of Suppliers in Supply Chains Using Fuzzy Logic
