The　aim　of　this　paper　is　to　develop　a　methodology　for　solving　multiattribute　decision　making　(MADM)　problems　in　which　weights　of　attributes　and　ratings　of　alternatives　on　qualitative　and　quantitative　attributes　are　expressed　with　intuitionistic　fuzzy　sets　(IFSs).　In　this　methodology,　relative　membership/satisfaction　and　non-membership/non-satisfaction　degrees　are　formulated　to　construct　IFSs　for　numerical　values　of　alternatives　on　quantitative　attributes.　Alternatives　on　qualitative　attributes　are　evaluated　using　linguistic　variables　and　semantics　which　are　parameterized　by　IFSs.　Hereby,　weights　and　ratings　of　alternatives　on　both　qualitative　attributes　and　quantitative　attributes　may　be　expressed　with　IFSs　in　a　unified　way.　The　generalized　ordered　weighted　averaging　(GOWA)　operator　is　further　extended　to　the　situations　in　which　the　argument　values　are　IFSs　and　thus　a　methodology　is　developed　to　solve　MADM　problems　using　IFSs.　Validity　and　applicability　of　the　proposed　methodology　in　this　paper　are　illustrated　with　a　real　numerical　example.　©　2010　Elsevier　Ltd.