def METHOD_NAME() -> None:
    params = ng.p.Tuple(ng.p.Scalar(lower=0, upper=2), ng.p.Scalar(lower=0, upper=2))
    loss_values = [[[0.0, 2.0], [1.0, 1.0]], [[0.0, 4.0], [1.0, 3.0], [3.0, 1.0]], [[2.0, 3.0], [4.0, 2.0]]]
    candidates: tp.List[p.Parameter] = []
    expected_frontiers = []
    for vals in loss_values:
        expected_frontier = []
        for v in vals:
            candidate = params.spawn_child().set_standardized_data(v)
            candidate._losses = np.array(v)
            candidates.append(candidate)
            expected_frontier.append(candidate)
        expected_frontiers.append(expected_frontier)
    ranking_method = nsga2.FastNonDominatedRanking()
    frontiers = ranking_method.compute_ranking(candidates)
    assert set(frontiers[0]) == set(expected_frontiers[0])
    assert set(frontiers[1]) == set(expected_frontiers[1])
    assert set(frontiers[2]) == set(expected_frontiers[2])