class_docstr: Hosaki objective function.
  
  This class defines the Hosaki [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Hosaki}}(x) = \left ( 1 - 8 x_1 + 7 x_1^2 - \frac{7}{3} x_1^3
      + \frac{1}{4} x_1^4 \right ) x_2^2 e^{-x_1}
  
  
  with :math:`x_i \in [0, 10]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = -2.3458115` for :math:`x = [4, 2]`.
  
  .. [1] Jamil, M. & Yang, X.-S. A Literature Survey of Benchmark Functions
  For Global Optimization Problems Int. Journal of Mathematical Modelling
  and Numerical Optimisation, 2013, 4, 150-194.
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code: def __init__(self, dimensions=2):
      Benchmark.__init__(self, dimensions)
  
      self._bounds = ([0.0, 5.0], [0.0, 6.0])
      self.custom_bounds = [(0, 5), (0, 5)]
  
      self.global_optimum = [[4, 2]]
      self.fglob = -2.3458115
  
imports: import numpy
  from numpy import abs, arctan2, asarray, cos, exp, arange, pi, sin, sqrt, sum
  from .go_benchmark import Benchmark
label_desc: Use image node_id 1 to create a new Hosaki object from inherited base classes: Benchmark with example: obj = Hosaki(dimensions)