class_docstr: Zacharov objective function.
  
  This class defines the Zacharov [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Zacharov}}(x) = \sum_{i=1}^{n} x_i^2 + \left ( \frac{1}{2}
                               \sum_{i=1}^{n} i x_i \right )^2
                               + \left ( \frac{1}{2} \sum_{i=1}^{n} i x_i 
                               \right )^4
  
  Here, :math:`n` represents the number of dimensions and
  :math:`x_i \in [-5, 10]` for :math:`i = 1, ..., n`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x_i = 0` for
  :math:`i = 1, ..., n`
  
  .. [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.
code: def __init__(self, dimensions=2):
      Benchmark.__init__(self, dimensions)
  
      self._bounds = list(zip([-5.0] * self.N, [10.0] * self.N))
      self.custom_bounds = ([-1, 1], [-1, 1])
  
      self.global_optimum = [[0 for _ in range(self.N)]]
      self.fglob = 0.0
      self.change_dimensionality = True
  
imports: from numpy import abs, sum, sign, arange
  from .go_benchmark import Benchmark
label_desc: Use image node_id 1 to create a new Zacharov object from inherited base classes: Benchmark with example: obj = Zacharov(dimensions)