In　the　classical　Linear　Programming　Technique　for　Multidimensional　Analysis　of　Preference　(LINMAP),　the　decision　maker　(DM)　gives　the　pair-wise　comparisons　of　alternatives　with　crisp　truth　degree　0　or　1.　However,　in　the　real　world,　DM　is　not　sure　enough　in　all　comparisons　and　can　express　his/her　opinion　with　some　fuzzy　truth　degree.　Thus,　DM＇s　preferences　are　given　through　pair-wise　comparisons　of　alternatives　with　fuzzy　truth　degrees,　which　may　be　represented　as　trapezoidal　fuzzy　numbers　(TrFNs).　Considered　such　fuzzy　truth　degrees,　the　aim　of　this　paper　is　to　develop　a　new　fuzzy　linear　programming　technique　for　solving　multiattribute　decision　making　(MADM)　problems　with　multiple　types　of　attribute　values　and　incomplete　weight　information.　In　this　method,　TrFNs,　real　numbers,　and　intervals　are　used　to　represent　the　multiple　types　of　decision　information.　The　fuzzy　consistency　and　inconsistency　indices　are　defined　as　TrFNs　due　to　the　alternatives＇　comparisons　with　fuzzy　truth　degrees.　Hereby　a　new　fuzzy　linear　programming　model　is　constructed　and　solved　by　the　possibility　linear　programming　method　with　TrFNs　developed　in　this　paper.　The　fuzzy　ideal　solution　(IS)　and　the　attribute　weights　are　then　obtained.　The　distances　of　alternatives　from　the　fuzzy　IS　can　be　calculated　to　determine　their　ranking　order.　The　implementation　process　of　the　method　proposed　in　this　paper　is　illustrated　with　a　strategy　partner　selection　example.　The　comparison　analyzes　show　that　the　method　proposed　in　this　paper　generalizes　the　classical　LINMAP,　fuzzy　LINMAP　and　possibility　LINMAP.　(C)　2013　Elsevier　B.V.　All　rights　reserved.