Solar　heat　pump　has　attracted　more　and　more　attention.　This　paper　aims　to　improve　the　performance　of　an　absorption　solar-ground　source　heat　pump　(ASGSHP)　through　multi-objective　optimization.　Firstly,　a　double-effect　absorption　heat　pump　module　is　developed　and　a　simulation　model　of　the　ASGSHP　is　established　on　TRNSYS　platform.　Secondly,　considering　both　the　economy　and　the　environmental　protection,　the　equivalent　uniform　annual　cost　(EUAC)　and　the　environmental　impact　load　(EIL)　are　taken　as　two　objective　functions.　The　non-dominated　sorting　genetic　algorithm　with　elite　strategy　(NSGA-II)　is　applied　to　optimize　the　environmental　and　economic　performance　of　the　ASGSHP　by　TRNSYS　and　MATLAB　joint.　Pareto　front　of　the　multi-objective　optimization　of　the　ASGSHP　system　is　obtained.　Thirdly,　using　the　TOPSIS　decision-making　method,　the　best　optimization　values　for　three　optimization　variables　including　the　solar　collector　area,　the　storage　tank　volume　and　the　setting　temperature　of　the　auxiliary　heater　are　obtained.　The　optimization　rate　of　the　environmental　impact　load　and　the　equivalent　uniform　annual　cost　of　the　optimal　point　selected　by　the　TOPSIS　decision-making　method　is　10.9%　and　3.4%,　respectively.　The　research　results　can　provide　the　basic　data　and　theoretical　guidance　for　the　further　development　and　utilization　of　the　solar-ground　source　heat　pump.