Waste-to-energy　technologies　compatible　with　recycling　are　promising　solutions　for　sustainable　municipal　waste　management　from　both　economic　and　environmental　perspectives.　This　study　focuses　on　the　economic　-environment-energy　(3E)　objective-driven　integrated　waste　management　optimization　problems　under　deep　complexities.　A　novel　multi-objective　programming　model　is　developed　to　assist　the　optimal　decision-making　with　the　consideration　of　system　profit,　greenhouse　gas　emission,　and　energy　recovery　simultaneously.　Be-sides,　it　advances　existing　optimization　methods　by　incorporating　interval-valued　fuzzy　numbers　to　tackle　the　ambiguity　and　the　essential　fuzziness　in　experts＇　judgment.　It　was　verified　by　a　case　study　from　an　urban　district　of　Beijing,　China.　The　optimum　waste　treatment　facility　planning　and　waste　stream　allocation　strategies　with　multi-objective　tradeoffs　were　obtained　to　support　decision-making　considering　different　preferences　of　impor-tance　ranking.　In　general,　incineration　and　anaerobic　digestion　would　be　the　main　technologies　for　waste　disposal　in　the　study　area.　Recycling　would　be　greatly　encouraged　when　pursuing　more　economic　profits　and　greenhouse　gas　emission　reduction.　With　withdrawing　the　subsidy　in　the　future,　the　investment　in　anaerobic　digestion　would　become　less　attractive.　Meanwhile,　the　landfill　with　gas　recovery　would　even　become　economically　infeasible　if　there　is　no　further　reduction　in　cost.　In　addition,　waste　source　separation　is　also　a　crucial　factor　for　successful　integrated　waste　management.　It　is　suggested　that　a　proper　government　subsidy　and　public　participation　in　waste　source　separation　would　guarantee　the　sustainable　development　of　the　integrated　waste　management　system.