This work suggests ordering alternatives under fuzzy multiple criteria decision making (MCDM) via a fuzzy number dominance based ranking approach,
where the ratings of alternatives versus qualitative criteria and the importance weights of all criteria are assessed in linguistic values represented by fuzzy numbers. The difference of one final fuzzy evaluation
value over another is used to represent the dominance degree of one alternative over another.
The membership function for the final fuzzy evaluation value of each lternative and the difference between each pair of final fuzzy evaluation values can be developed through α-cuts and nterval arithmetic of fuzzy numbers. Formulas for the dominance degree can be clearly derived based on
the developed membership function via integral development. A simple anking procedure based on these dominance degrees is then proposed to order
the alternatives. Finally a numerical example demonstrates the feasibility of the proposed model.