class_docstr: HimmelBlau objective function.
  
  This class defines the HimmelBlau [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{HimmelBlau}}({x}) = (x_1^2 + x_2 - 11)^2 + (x_1 + x_2^2 - 7)^2
  
  
  with :math:`x_i \in [-6, 6]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x = [3, 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 = list(zip([-5.0] * self.N, [5.0] * self.N))
  
      self.global_optimum = [[3.0, 2.0]]
      self.fglob = 0.0
  
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 HimmelBlau object from inherited base classes: Benchmark with example: obj = HimmelBlau(dimensions)