In　allusion　to　dynamic　intuitionistic　normal　fuzzy　multi-attribute　decision-making　(MADM)　problems　with　unknown　time　weight,　a　MADM　method　based　on　dynamic　intuitionistic　normal　fuzzy　aggregation　(DINFA)　operators　and　VIKOR　method　with　time　sequence　preference　was　presented.　In　this　method,　two　information　aggregating　operators　were　first　proposed　and　proved,　including　dynamic　intuitionistic　normal　fuzzy　weighted　arithmetic　average　(DINFWAA)　operator　and　dynamic　intuitionistic　normal　fuzzy　weighted　geometric　average　(DINFWGA)　operator.　Meanwhile,　we　constructed　a　multi-target　nonlinear　programming　model,　which　fused　time　degree　theory　that　was　based　on　subjective　preference　and　information　entropy　principle　based　on　objective　preference,　to　obtain　time　weight,　Based　on　which,　according　to　the　algorithm　of　intuitionistic　normal　fuzzy　number,　intuitionistic　normal　fuzzy　information　under　different　time　sequences　were　aggregated　by　using　the　proposed　DINFA　operators,　and　formed　a　dynamic　intuitionistic　normal　fuzzy　comprehensive　decision-making　matrix;　then,　obtained　the　optimal　solution　that　was　the　closest　to　ideal　solution　via　VIKOR　method.　Finally,　the　feasibility　and　significance　of　the　presented　method　over　existing　methods　were　verified　via　analysis　of　numerical　examples.　(C)　2017　Elsevier　Ltd.　All　rights　reserved.