Set_normalized_coefficient in JuMP.jl is slow

Specific Domains Optimization (Mathematical)
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6

r is a scalar?

How about something like:

    model = direct_model(HiGHS.Optimizer())
    set_silent(model)
    @variable(model, x[i = 1:N] >= lb[i])
    @variable(model, y[i = 1:N])
    @objective(model, Min, l' * x)
    @constraint(model, con[i in 1:N], 1 * x[i] - y[i] == 0)
    @constraint(model, B * x - A * y .>= d)
    for r in range(0, 1, length = n)
        set_normalized_coefficient(con, x, fill(1 + r, N))
        optimize!(model)
    end

Now you only need to modify N coefficients in each step.

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