In　order　to　balance　the　temporal-spatial　distribution　of　urban　traffic　flow,　a　model　is　established　for　combined　urban　traffic　signal　control　and　traffic　flow　guidance.　With　consideration　of　the　wide　use　of　fixed　signal　control　at　intersections,　traffic　assignment　under　traffic　flow　guidance,　and　dynamic　characteristics　of　urban　traffic　management,　a　tri-level　programming　model　is　presented.　To　reflect　the　impact　of　intersection　delay　on　traffic　assignment,　the　lower　level　model　is　set　as　a　modified　user　equilibrium　model.　The　middle　level　model,　which　contains　several　definitional　constraints　for　different　phase　modes,　is　built　for　the　traffic　signal　control　optimization.　To　solve　the　problem　of　tide　lane　management,　the　upper　level　model　is　built　up　based　on　nonlinear　0-1　integer　programming.　A　heuristic　iterative　optimization　algorithm　(HIOA)　is　set　up　to　solve　the　tri-level　programming　model.　The　lower　level　model　is　solved　by　method　of　successive　averages　(MSA),　the　middle　level　model　is　solved　by　non-dominated　sorting　genetic　algorithm　II　(NSGA　II),　and　the　upper　level　model　is　solved　by　genetic　algorithm　(GA).　A　case　study　is　raised　to　show　the　efficiency　and　applicability　of　the　proposed　modelling　and　computing　method.