Most of the integrated methods of multi-attributes decision making (MADM) used type-1 fuzzy sets to represent uncertainties. Recent theory has suggested that interval type-2 fuzzy sets (IT2 FS) could be used to enhance representation of uncertainties in decision making problems. Differently from the typical integrated MADM methods which directly used type-1 fuzzy sets, this paper proposes an integrating simple additive weighting – technique for order preference similar to ideal solution (SAW-TOPSIS) based on IT2 FS to enhance judgment. The SAW with IT2 FS is used to determine the weight for each criterion, while TOPSIS method with IT2 FS is used to obtain the final ranking for the attributes. A numerical example is used to illustrate the proposed method. The numerical results show that the proposed integrating method is feasible in solving MADM problems under complicated fuzzy environments. In essence, the integrating SAW-TOPSIS is equipped with IT2 FS in contrast to type-1 fuzzy sets for solving MADM problems. The proposed method would make a great impact and significance for the practical implementation. Finally, this paper provides some recommendations for future research directions.