class_docstr: Mishra 2 objective function.
  
  This class defines the Mishra 2 [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Mishra02}}({x}) = (1 + x_n)^{x_n}
  
  
   with
  
   .. math::
  
       x_n = n - \sum_{i=1}^{n-1} \frac{(x_i + x_{i+1})}{2}
  
  
  Here, :math:`n` represents the number of dimensions and
  :math:`x_i \in [0, 1]` for :math:`i = 1, ..., n`.
  
  *Global optimum*: :math:`f(x) = 2` for :math:`x_i = 1`
  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.
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code: def __init__(self, dimensions=2):
      Benchmark.__init__(self, dimensions)
  
      self._bounds = list(zip([0.0] * self.N, [1.0 + 1e-9] * self.N))
  
      self.global_optimum = [[1.0 for _ in range(self.N)]]
      self.fglob = 2.0
      self.change_dimensionality = True
  
imports: from numpy import abs, asarray, cos, exp, log, arange, pi, prod, sin, sqrt, sum, tan
  from .go_benchmark import Benchmark, safe_import
label_desc: Use image node_id 1 to create a new Mishra02 object from inherited base classes: Benchmark with example: obj = Mishra02(dimensions)