# Add noise in the constraint matrix

`SDDP.jl`

supports coefficients in the constraint matrix through the `JuMP.set_normalized_coefficient`

function.

```
julia> model = SDDP.LinearPolicyGraph(
stages=3, lower_bound = 0, optimizer = HiGHS.Optimizer
) do subproblem, t
@variable(subproblem, x, SDDP.State, initial_value = 0.0)
@constraint(subproblem, emissions, 1x.out <= 1)
SDDP.parameterize(subproblem, [0.2, 0.5, 1.0]) do ω
JuMP.set_normalized_coefficient(emissions, x.out, ω)
println(emissions)
end
@stageobjective(subproblem, -x.out)
end
A policy graph with 3 nodes.
Node indices: 1, 2, 3
julia> SDDP.simulate(model, 1);
emissions : x_out <= 1
emissions : 0.2 x_out <= 1
emissions : 0.5 x_out <= 1
```

JuMP will normalize constraints by moving all variables to the left-hand side. Thus, `@constraint(model, 0 <= 1 - x.out)`

becomes `x.out <= 1`

. `JuMP.set_normalized_coefficient`

sets the coefficient on the *normalized* constraint.