import HiGHS
import Ipopt
import Juniper

using JuMP

function test()

    optimizer = Juniper.Optimizer
    nl_solver= optimizer_with_attributes(Ipopt.Optimizer,
                                         "print_level" => 0)
    mip_solver = optimizer_with_attributes(HiGHS.Optimizer,
                                           "output_flag" => true)
    model = Model(optimizer_with_attributes(
        optimizer,
        "nl_solver"=>nl_solver,
        "mip_solver"=>mip_solver,
        "log_levels"=>[:Info, :Table, :Timing, :AllOptions]))

    # 6 fails. 5 works.
    problem_size = 6

    # x .>= 0, sum(x) >= 4
    @variable(model, x[1:problem_size], integer=true)
    @constraint(model, x .>= zeros(Int, problem_size))
    @constraint(model, sum(x[i] for i in 1:problem_size) >= 4)

    # Minimize sum(x.^2)
    # Works if integer = false>
    @variable(model, x_squared[1:problem_size], integer=true)
    for i in 1:problem_size
        @NLconstraint(model, x_squared[i] == x[i] ^ 2)
    end

    @NLobjective(model, Min,
                 x_squared[1]
                 + x_squared[2]
                 + x_squared[3]
                 + x_squared[4]
                 + x_squared[5]
                 + x_squared[6])

    # Also fails.
    #@NLobjective(model, Min, sum(x_squared[i] for i in 1:problem_size))

    optimize!(model)

    #=
    @show termination_status(model)
    @show primal_status(model)
    solution_summary(model)
    println(value.(model[:x]))
    =#

    return model

end

@time m = test()