class_docstr: Price 3 objective function.
  
  This class defines the Price 3 [1]_ global optimization problem. This is a
  multimodal minimization problem defined as follows:
  
  .. math::
  
     f_{\text{Price03}}(x) = 100(x_2 - x_1^2)^2 + \left[6.4(x_2 - 0.5)^2
     - x_1 - 0.6 \right]^2
  
  with :math:`x_i \in [-50, 50]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x = [-5, -5]`,
  :math:`x = [-5, 5]`, :math:`x = [5, -5]`, :math:`x = [5, 5]`.
  
  .. [1] Price, W. A controlled random search procedure for global
  optimisation Computer Journal, 1977, 20, 367-370
  
  TODO Jamil #96 has an erroneous factor of 6 in front of the square brackets
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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.custom_bounds = ([0, 2], [0, 2])
  
      self.global_optimum = [[1.0, 1.0]]
      self.fglob = 0.0
  
imports: from numpy import abs, sum, sin, cos, sqrt, log, prod, where, pi, exp, arange, floor, log10, atleast_2d, zeros
  from .go_benchmark import Benchmark
label_desc: Use image node_id 1 to create a new Price03 object from inherited base classes: Benchmark with example: obj = Price03(dimensions)