In　the　municipal　solid　waste　(MSW)　management　system,　there　are　many　uncertainties　associated　with　the　coefficients　and　their　impact　factors.　Uncertainties　can　be　normally　presented　as　both　membership　functions　and　probabilistic　distributions.　This　study　develops　a　scenario-based　fuzzy-stochastic　quadratic　programming　(SFQP)　model　for　identifying　an　optimal　MSW　management　policy　and　for　allowing　dual　uncertainties　presented　as　probability　distributions　and　fuzzy　sets　being　communicated　into　the　optimization　process.　It　can　also　reflect　the　dynamics　of　uncertainties　and　decision　processes　under　a　complete　set　of　scenarios.　The　developed　method　is　applied　to　a　case　study　of　long-term　MSW　management　and　planning.　The　results　indicate　that　reasonable　solutions　have　been　generated.　They　are　useful　for　identifying　desired　waste-flow-allocation　plans　and　making　compromises　among　system　cost,　satisfaction　degree,　and　constraint-violation　risk.　©　2011　Elsevier　Inc.