Nowadays,　the　rapidly　increasing　healthcare　cost　has　become　a　serious　problem　because　of　inefficient　usage　of　medical　resources.　The　Emergency　Department　(ED)　plays　a　vital　role　in　the　hospital　system　and　has　critical　effects　on　the　overall　efficiency　in　a　hospital.　The　ED　deals　with　patient’s　arrival,　triage,　physician　assessment,　imaging　and　laboratory　studies,　treatment　planning,　nursing　procedures,　decisions　to　discharge　or　admit　access　to　inpatient　beds　and　physicians.　These　activities　generally　occur　in　a　sequential　manner　and　the　delayed　activities　of　the　patient　flow　can　cause　bottlenecking　and　reduce　the　service　level.　Optimising　the　service　of　the　ED　is　challenging　because　the　arrival　times　of　patients　are　dynamic　and　their　expected　treatment　times　are　volatile.　This　paper　develops　a　new　ED　optimisation　model　using　stochastic　mathematical　programming　approach　under　limited　budget　and　resource　capacity.　The　objectives　of　the　proposed　model　are　for　increasing　the　system　efficiency,　serving　more　patients　in　specific　time,　or　providing　the　same　quality　of　the　service　with　the　use　of　less　medical　resources.　A　numerical　investigation　is　presented　and　demonstrates　that　high-quality　solutions　are　obtainable　for　industry-scale　applications　in　a　reasonable　time.　Computational　experiments　have　been　conducted　using　CPLEX　and　ExtendSim　to　solve　the　ED-Stochastic　Optimisation　Mixed　Integer　Programming　model　and　ED-Simulation　model　sequentially.　Real　data　for　Royal　Brisbane　and　Women＇s　Hospital　(RBWH)　is　used　in　this　paper　to　validate　the　proposed　solution　approach.　©　2017　Proceedings　-　22nd　International　Congress　on　Modelling　and　Simulation,　MODSIM　2017.　All　rights　reserved.