Supplier selection in risk consideration: a fuzzy based topsis approach

Abstract

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain. In classical Multi-Criteria Decision Making (MCDM) methods, the ratings and the weights of the criteria are known precisely. Owning to vagueness of the decision data, the crisp data are inadequate for real-life situations. Since human judgments including preferences are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in decision making is deemed to be relevant. On the other hand, it is a hard problem since supplier selection is typically a MCDM problem involving several conflicting criteria on which decision maker’s knowledge is usually vague and imprecise. In the present work, a risk-based suppliers’ evaluation module is proposed. Linguistic values are used to assess the ratings and weights for the risk based supplier selection factors. These linguistic ratings can be expressed in triangular fuzzy numbers. Then, a hierarchy MCDM model based on fuzzy-sets theory is proposed to deal with the supplier selection problems in the supply chain system. According to the concept of the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), a closeness coefficient is defined to determine the ranking order of all suppliers by calculating the both fuzzy positive-ideal solution and fuzzy negative-ideal solution, simultaneously. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the decision-support systems in appropriate situation.