class_docstr: A BenchmarkProblem support multiple objectives. Rather than knowing each
  objective's optimal value we track a known maximum hypervolume computed from a
  given reference point.
code: def __init__(
      self,
      maximum_hypervolume: float,
      reference_point: List[float],
      *,
      name: str,
      search_space: SearchSpace,
      optimization_config: OptimizationConfig,
      runner: Runner,
      num_trials: int,
      infer_noise: bool,
      tracking_metrics: Optional[List[Metric]] = None,
  ) -> None:
      self.maximum_hypervolume = maximum_hypervolume
      self.reference_point = reference_point
      super().__init__(
          name=name,
          search_space=search_space,
          optimization_config=optimization_config,
          runner=runner,
          num_trials=num_trials,
          infer_noise=infer_noise,
          tracking_metrics=tracking_metrics,
      )
  
imports: import abc
  from typing import Any, Dict, List, Optional, Protocol, runtime_checkable, Type
  from ax.core.metric import Metric
  from ax.core.objective import MultiObjective, Objective
  from ax.core.optimization_config import MultiObjectiveOptimizationConfig, ObjectiveThreshold, OptimizationConfig
  from ax.core.outcome_constraint import OutcomeConstraint
  from ax.core.parameter import ParameterType, RangeParameter
  from ax.core.runner import Runner
  from ax.core.search_space import SearchSpace
  from ax.core.types import ComparisonOp
  from ax.metrics.botorch_test_problem import BotorchTestProblemMetric
  from ax.runners.botorch_test_problem import BotorchTestProblemRunner
  from ax.utils.common.base import Base
  from ax.utils.common.typeutils import checked_cast
  from botorch.test_functions.base import BaseTestProblem, ConstrainedBaseTestProblem
  from botorch.test_functions.multi_objective import MultiObjectiveTestProblem
  from botorch.test_functions.synthetic import SyntheticTestFunction
label_desc: Use image node_id 1 to create a new MultiObjectiveBenchmarkProblem object from inherited base classes: BenchmarkProblem with example: obj = MultiObjectiveBenchmarkProblem(maximum_hypervolume, reference_point)