The　organic　Rankine　cycle　(ORC)　system　is　an　important　technology　for　recovering　energy　from　the　waste　heat　of　internal　combustion　engines,　which　is　of　significant　importance　for　the　improvement　of　fuel　utilization.　This　study　analyses　the　performance　of　vehicle　ORC　systems　and　proposes　a　rapid　optimization　method　for　enhancing　vehicle　ORC　performance.　This　study　constructed　a　numerical　simulation　model　of　an　internal　combustion　engine-ORC　waste　heat　recovery　system　based　on　GT-Suite　software　v2016.　The　impact　of　key　operating　parameters　on　the　performance　of　two　organic　Rankine　cycles:　the　simple　organic　Rankine　cycle　(SORC)　and　the　recuperative　organic　Rankine　cycle　(RORC)　was　investigated.　In　order　to　facilitate　real-time　prediction　and　optimization　of　system　performance,　a　data-driven　rapid　prediction　model　of　the　performance　of　the　waste　heat　recovery　system　was　constructed　based　on　an　artificial　neural　network.　Meanwhile,　the　NSGA-II　multi-objective　algorithm　was　used　to　investigate　the　competitive　relationship　between　different　performance　objective　functions.　Furthermore,　the　optimal　operating　parameters　of　the　system　were　determined　by　utilizing　the　TOPSIS　method.　The　results　demonstrate　that　the　highest　thermal　efficiencies　of　the　SORC　and　RORC　are　6.21%　and　8.61%,　respectively,　the　highest　power　outputs　per　unit　heat　transfer　area　(POPAs)　are　6.98　kW/m2　and　8.99　kW/m2,　respectively,　the　lowest　unit　electricity　production　costs　(EPC)　are　7.22　x　10-2　USD/kWh　and　3.15　x　10-2　USD/kWh,　respectively,　and　the　lowest　CO2　emissions　are　2.85　ton　CO2,eq　and　3.11　ton　CO2,eq,　respectively.　The　optimization　results　show　that　the　RORC　exhibits　superior　thermodynamic　and　economic　performance　in　comparison　to　the　SORC,　yet　inferior　environmental　performance.