A　multi-attribute　decision-making　method　based　on　heterogeneous　information　and　set　pair　analysis　is　proposed,　considering　the　balance　of　the　contradictions　between　information　representation　and　information　processing　in　the　decision-making　process.　The　method　is　applied　to　decision-making　problems　in　which　the　attribute　weights　are　completely　unknown　and　the　attribute　values　are　characterized　as　heterogeneous　information　(including　exact　numbers,　interval　numbers,　intuitionistic　fuzzy　numbers,　interval　intuitionistic　fuzzy　numbers,　neutrosophic　numbers,　interval　neutrosophic　numbers,　picture　fuzzy　numbers,　and　Pythagorean　fuzzy　numbers).　First,　various　transformation　methods　for　converting　heterogeneous　information　into　the　connection　numbers　(CNs)　of　set　pair　analysis　are　introduced　and　defined,　and　the　heterogeneous　information　is　uniformly　converted　into　CNs　for　ease　of　processing.　Second,　the　attribute　weights　of　the　heterogeneous　information　are　obtained　using　the　information　entropy　of　the　CNs.　Thereafter,　the　alternatives　are　ranked　by　the　VIKOR　method.　Moreover,　we　use　the　method　of　setting　a　threshold　for　the　compromise　evaluation　value,　and　the　clustering　method　to　group　the　alternatives　to　provide　more　auxiliary　decision　making.　Finally,　the　feasibility　and　effectiveness　of　the　proposed　method　are　demonstrated　by　a　typhoon　disaster　evaluation　example,　and　the　advantages　of　the　proposed　approach　are　emphasized　by　performing　a　multi-faceted　comparative　analysis　with　other　methods.　Among　them,　the　time　complexity　of　the　proposed　algorithm　can　be　simplified　as　O(m)　,　which　demonstrates　an　improvement　on　the　simplified　time　complexity　O(m2)　of　the　two　existing　methods.　Particularly　in　the　context　of　big　data,　the　advantages　are　apparent.　©　2022,　The　Author(s),　under　exclusive　licence　to　Springer-Verlag　GmbH　Germany,　part　of　Springer　Nature.