One　of　the　most　critical　objectives　in　the　healthcare　system　is　maximising　patient　flows　in　the　emergency　care　patient　pathway.　Patient　emergency　flow　analysis　indicates　that　the　timetabling　of　a　patient＇s　movement　from　one　activity　to　another　through　the　Emergency　Department　(ED)　is　critical　for　treating　patients.　The　ED　deals　with　the　patient＇s　arrival,　triage,　physician　assessment,　imaging　and　laboratory　studies,　treatment　planning,　nursing　procedures,　and　decisions　to　admit　or　discharge　the　patient.　Any　delayed　activities　in　patient　flow　reduce　the　service　level　of　healthcare.　To　address　these　challenges,　this　paper　develops　a　stochastic　ED　Simulation-Optimisation　approach　by　considering　stochastic　variables,　such　as　patient　interarrival　times　and　treatment　times,　using　statistical　distributions.　This　type　of　distribution　depends　on　two　main　elements:　day　shifts　and　patient　categories.　A　hybrid　evolutionary　algorithm　is　integrated　with　the　simulation　to　find　a　satisfactory　solution　for　this　stochastic　optimisation　problem　in　real　time.　Computational　experiments　show　that　the　proposed　approach　can　serve　more　patients　in　specific　time　windows　or　provide　the　same　quality　of　the　service　with　the　use　of　fewer　medical　resources.