Vendor Selection Using a New Fuzzy Group TOPSIS Approach

Nowadays vendor (supplier) selection has turned to an important decision-making challenge for top decisionmakers in companies; this is because an inappropriate decision affects not only that specific buyer but also the entire supply chain. In the real-world situations, due to incomplete and vague information, required data for decision making often can not be described deterministically, and are usually imprecise in nature. Therefore, in order to make more realistic decisions, fuzzy sets theory can be applied in such cases. In this paper, we propose a new fuzzy multiple criteria group decision making (FMCGDM) approach based on technique for order preference by similarity to ideal solution (TOPSIS) method for evaluating and selecting an appropriate vendor, where the ratings of each alternative and importance weight of each criterion are expressed in trapezoidal fuzzy numbers. Furthermore, we use the canonical representation of multiplication operation on three trapezoidal fuzzy numbers to construct the weighted normalized decision matrix. Finally, to clearly illustrate our approach a numerical example is conducted. © 2009 World Academic Press, UK. All rights reserved.