In　this　study,　an　interval-parameter　robust　minimax-regret　programming　method　is　developed　and　applied　to　the　planning　of　energy　and　environmental　systems.　Methods　of　robust　programming,　interval-parameter　programming,　and　minimax-regret　analysis　are　incorporated　within　a　general　optimization　framework　to　enhance　the　robustness　of　the　optimization　effort.　The　interval-parameter　robust　minimax-regret　programming　can　deal　with　uncertainties　expressed　as　discrete　intervals,　fuzzy　sets,　and　random　variables.　It　can　also　be　used　for　analyzing　multiple　scenarios　associated　with　different　system　costs　and　risk　levels.　In　its　solution　process,　the　fuzzy　decision　space　is　delimited　into　a　more　robust　one　through　dimensional　enlargement　of　the　original　fuzzy　constraints;　moreover,　an　interval-element　cost　matrix　can　be　transformed　into　an　interval-element　regret　matrix,　such　that　the　decision　makers　can　identify　desired　alternatives　based　on　the　inexact　minimax　regret　criterion.　The　developed　method　has　been　applied　to　a　case　study　of　energy　and　environmental　systems　planning　under　uncertainty.　The　results　indicate　that　reasonable　solutions　have　been　generated.