Current　buildings　are　facing　different　environmental　demands,　such　as　improving　thermal　comfort　and　energy　efficiency　and　reducing　exergy　loss.　However,　conventional　mixing　ventilation　(MV)　cannot　satisfy　the　different　demands;　therefore,　advanced　ventilation　modes　utilizing　a　non-uniform　environment　have　gained　attention.　Multiple　scenarios　with　different　occupant　activity　levels　cause　difficulties　in　ventilation　control.　For　these　multi　factor　and　multi-objective　oriented　problems,　two　issues　exist:　1)　how　to　change　the　operational　mode　when　the　scenarios　and　demands　change　simultaneously,　and　2)　how　to　evaluate　the　overall　ventilation　performance　under　different　scenarios　and　demand　conditions.　Therefore,　this　study　proposes　an　approach　for　assisting　in　the　decision　making　of　ventilation　strategies　in　different　scenarios　under　single　or　multiple　demand　conditions.　Using　a　typical　office,　three　occupancy　conditions　were　predesigned　by　combining　MV,　displacement　ventilation　(DV),　and　stratum　ventilation　(SV)　solutions.　Computational　fluid　dynamics　simulations　were　performed　to　calculate　the　indicators　for　a　single　demand,　namely,　heat　removal　efficiency　(HRE),　contaminant　removal　efficiency　(CRE),　air　diffusion　performance　index　(ADPI),　and　modified　index　of　mixing　(IOM*).　In　the　case　of　multiple　demands,　the　Z-score　was　applied　for　standardization　and　ranking.　The　result　showed　that　different　scenarios　with　different　demand　orientations　require　different　ventilation　modes.　Taking　the　HRE　and　IOM*　as　objectives,　DV　performed　best　for　the　scenario　of　independent　working,　whereas　SV　performed　best　for　discussion　and　meeting.　When　considering　four　demands　simultaneously,　SV　performed　best　in　the　scenario　of　meeting,　while　MV　performed　best　in　the　remaining　scenarios.　This　study　has　verified　the　effectiveness　of　using　a　multi-indicator　evaluation　method　for　ventilation　strategy　optimization　under　multi-factor　and　multi-scenario　conditions.