[TestMethod]
    [ExpectedException(typeof(AssertFailedException))]
    public void AugmentedLagrangianSolverTest02()
    {

        // Ensure that the Accord.NET random generator starts from a particular fixed seed.
        Accord.Math.Random.Generator.Seed = 0;

        // The minimization problem is to minimize the function (x_0 - 1)^2 + (x_1 - 2.5)^2$ subject
        // to the five constraints $x_0 - 2x_1 +2 \ge 0$, $-x_0 - 2x_1 + 6 \ge0$, $-x_0 + 2x_1 + 2\ge0$,
        // $x_0\ge0$ and $x_1\ge0$.

        var f = new NonlinearObjectiveFunction(2,
            function: (x) => (x[0] - 1.0) * (x[0] - 1.0) + (x[1] - 2.5) * (x[1] - 2.5),
            gradient: (x) => new[] { 2.0 * (x[0] - 1.0), 2.0 * (x[1] - 2.5) } );

        var constraints = new List<NonlinearConstraint>();

        // Add the constraint $x_1 - 2x_2 + 2 \ge0$.
        constraints.Add(new NonlinearConstraint(f,
            function: (x) => x[0] - 2.0 * x[1] + 2.0,
            gradient: (x) => new[] { 1.0, -2.0 },
            shouldBe: ConstraintType.GreaterThanOrEqualTo, value: 0 ));

        // Add the constraint $-x_0 - 2x_1 + 6 \ge 0$.
        constraints.Add(new NonlinearConstraint(f,
            function: (x) => - x[0] - 2.0 * x[1] + 6.0,
            gradient: (x) => new[] { -1.0, -2.0 },
            shouldBe: ConstraintType.GreaterThanOrEqualTo, value: 0));

        // Add the constraint $-x_0 + 2x_1 + 2 \ge 0$.
        constraints.Add(new NonlinearConstraint(f,
            function: (x) => -x[0] + 2.0 * x[1] + 2.0,
            gradient: (x) => new[] { -1.0, 2.0 },
            shouldBe: ConstraintType.GreaterThanOrEqualTo, value: 0));

        // Add the constraint $x_0  \ge 0$.
        constraints.Add(new NonlinearConstraint(f,
            function: (x) => x[0],
            gradient: (x) => new[] { 1.0, 0.0 },
            shouldBe: ConstraintType.GreaterThanOrEqualTo, value: 0));

        // Add the constraint $x_1  \ge 0$.
        constraints.Add(new NonlinearConstraint(f,
            function: (x) => x[1],
            gradient: (x) => new[] { 0.0, 1.0 },
            shouldBe: ConstraintType.GreaterThanOrEqualTo, value: 0));

        var solver = new AugmentedLagrangian(f, constraints);

        Assert.IsTrue(solver.Minimize());
        double minValue = solver.Value;

        Assert.IsFalse(Double.IsNaN(minValue));

        // According to the example, the solution is $(1.4, 1.7)$.
        Assert.AreEqual(1.4, solver.Solution[0], 1e-5);
        Assert.AreEqual(1.7, solver.Solution[1], 1e-5);
    }