In　this　study,　a　constraint-softened　interval-fuzzy　linear　programming　(CS-IFLP)　method　is　developed　for　violation　analysis　of　environmental　management　systems　under　uncertainty.　CS-IFLP　can　deal　with　uncertainties　presented　in　terms　of　fuzzy　sets　and　intervals.　Moreover,　a　number　of　fuzzy　relaxation　levels　for　system　constraints　are　allowed,　such　that　the　relevant　decision　space　can　be　expanded.　This　can　help　generate　a　range　of　decision　alternatives　under　various　system　conditions,　and　facilitate　in-depth　analyses　of　tradeoffs　among　economic　objective,　satisfaction　degree,　and　constraint-violation　risk.　The　developed　method　is　applied　to　a　case　study　of　long-term　municipal　solid　waste　management　planning.　Results　indicate　that　reasonable　solutions　for　both　binary　and　continuous　variables　have　been　generated.　A　higher　relaxation　level　could　result　in　a　lower　system　cost　and　a　higher　satisfaction　degree,　but　with　a　higher　constraint-violation　risk.　Results　of　the　sensitivity　analyses　demonstrate　that　violated　system　constraints　have　various　effects　on　the　system　cost　and　satisfaction　degree.　©　Copyright　2009,　Mary　Ann　Liebert,　Inc.