Extension of the expected value method for multiple attribute decision making with fuzzy data

This paper is concerned with a method for multiple attribute decision making under fuzzy environment, in which the preference values take the form of triangular fuzzy numbers. Based on the idea that the attribute with a larger deviation value among alternatives should be assessed a larger weight, a linear programming model about the maximal deviation of weighted attribute values is established. Therefore, an approach to deal with attribute weights which are completely unknown is developed by using expected value operator of fuzzy variables. Furthermore, in order to make a decision or choose the optimum alternative, an expected value method is presented under the assumption that attribute weights are known fully. The method not only avoids complex comparing for fuzzy numbers, but also has the advantages of simple operation and easy calculation. Finally, a numerical example is used to illustrate the proposed approach at the end of this paper. (C) 2008 Elsevier B.V. All rights reserved.