An　approach　based　on　regret　theory　with　hesitant　fuzzy　analysis　is　presented　in　a　context　of　multiattribute　matching　decision　making　where　the　relative　weights　are　uncertain.　There　are　two　steps　being　addressed　in　this　approach.　First,　we　put　forward　a　maximizing　differential　model　to　determine　the　relative　weights　of　hesitant　fuzzy　attributes,　and　calculate　collective　utilities　of　each　attribute　according　to　regret　theory.　The　matching　satisfaction　degrees　(MSDs)　are　then　acquired　by　aggregating　the　collective　utilities　with　relative　weights.　Secondly,　an　optimal　matching　model　is　programmed　to　generate　the　matching　results　based　on　the　MSDs.　This　model　belongs　to　a　sort　of　multiobjective　assignment　problem　and　can　be　solved　using　the　min–max　method.　A　case　study　of　matching　outsourcing　contractors　and　providers　in　Fuzhou　National　Hi-tech　Zone　is　conducted　to　demonstrate　the　proposed　approach　and　its　potential　applications.　©　2016,　Taiwan　Fuzzy　Systems　Association　and　Springer-Verlag　Berlin　Heidelberg.