class_docstr: Blend Crossover operation used by :class:`~optuna.samplers.NSGAIISampler`.
  
  Uniformly samples child individuals from the hyper-rectangles created
  by the two parent individuals. For further information about BLX-alpha crossover,
  please refer to the following paper:
  
  - `Eshelman, L. and J. D. Schaffer.
    Real-Coded Genetic Algorithms and Interval-Schemata. FOGA (1992).
    <https://www.sciencedirect.com/science/article/abs/pii/B9780080948324500180>`_
  
  Args:
      alpha:
          Parametrizes blend operation.
code: def __init__(self, alpha: float = 0.5) -> None:
      self._alpha = alpha
  
file_path: optuna/optuna/samplers/nsgaii/_crossovers/_blxalpha.py
imports: import numpy
  from optuna._experimental import experimental_class
  from optuna.samplers.nsgaii._crossovers._base import BaseCrossover
  from optuna.study import Study
label_desc: Use image node_id 1 to create a new BLXAlphaCrossover object from inherited base classes: BaseCrossover with example: obj = BLXAlphaCrossover(alpha)