def METHOD_NAME() -> None:
    study = optuna.multi_objective.create_study(["maximize", "maximize"])
    def objective(trial: optuna.multi_objective.trial.MultiObjectiveTrial) -> Tuple[float, float]:
        p0 = trial.suggest_float("p0", -10, 10)
        p1 = trial.suggest_float("p1", 3, 5)
        p2 = trial.suggest_float("p2", 0.00001, 0.1, log=True)
        p3 = trial.suggest_float("p3", 100, 200, step=5)
        p4 = trial.suggest_int("p4", -20, -15)
        p5 = trial.suggest_categorical("p5", [7, 1, 100])
        p6 = trial.suggest_float("p6", -10, 10, step=1.0)
        p7 = trial.suggest_int("p7", 1, 7, log=True)
        return (
            p0 + p1 + p2,
            p3 + p4 + p5 + p6 + p7,
        )
    study.optimize(objective, n_trials=10)