Due　to　the　harsh　fact　that　existing　bilateral　matching　required　preference　ordinals　of　opposite　side　members　are　provided　by　each　agent,　a　novel　method　is　developed.　Agents　provide　evaluation　in　form　of　the　intuitionistic　fuzzy　set　through　a　pairwise　comparison　of　alternatives,　then　generating　an　intuitionistic　fuzzy　preference　relation　of　agents　when　applied　to　whole.　By　use　of　the　improved　minimum　logarithmic　square　algorithm,　the　satisfaction　degree　of　each　agent　is　calculated　based　on　the　intuitionistic　fuzzy　preference　relations(IFPR).　Furthermore,　a　single-object　optimization　model　with　stability　constraint　is　developed,　which　maximizes　satisfaction　degree　on　both　two　sides＇　agents.　The　results　can　be　obtained　by　solving　this　model.　Finally,　a　numerical　example　is　given　to　illustrate　the　feasibility　and　effectiveness　of　this　method.　©　2015,　Northeast　University.　All　right　reserved.