class_docstr: Mishra 9 objective function.
  
  This class defines the Mishra 9 [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
     f_{\text{Mishra09}}({x}) = \left[ ab^2c + abc^2 + b^2
     + (x_1 + x_2 - x_3)^2 \right]^2
  
  
  Where, in this exercise:
  
  .. math::
  
      \begin{cases} a = 2x_1^3 + 5x_1x_2 + 4x_3 - 2x_1^2x_3 - 18 \\
      b = x_1 + x_2^3 + x_1x_2^2 + x_1x_3^2 - 22 \\
      c = 8x_1^2 + 2x_2x_3 + 2x_2^2 + 3x_2^3 - 52 \end{cases}
  
  
  with :math:`x_i \in [-10, 10]` for :math:`i = 1, 2, 3`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x = [1, 2, 3]`
  
  .. [1] Mishra, S. Global Optimization by Differential Evolution and
  Particle Swarm Methods: Evaluation on Some Benchmark Functions.
  Munich Personal RePEc Archive, 2006, 1005
  
  TODO Line 1103
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code: def fun(self, x, *args):
      self.nfev += 1
  
      a = (
          2 * x[0] ** 3
          + 5 * x[0] * x[1]
          + 4 * x[2]
          - 2 * x[0] ** 2 * x[2]
          - 18
      )
      b = x[0] + x[1] ** 3 + x[0] * x[1] ** 2 + x[0] * x[2] ** 2 - 22.0
      c = (
          8 * x[0] ** 2
          + 2 * x[1] * x[2]
          + 2 * x[1] ** 2
          + 3 * x[1] ** 3
          - 52
      )
  
      return (
          a * c * b**2
          + a * b * c**2
          + b**2
          + (x[0] + x[1] - x[2]) ** 2
      ) ** 2
  
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 2 for calling the Mishra09 obj's underlying member method code with example usage: obj.fun(x) and returns: unknown