class_docstr: Plateau objective function.
  
  This class defines the Plateau [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Plateau}}(x) = 30 + \sum_{i=1}^n \lfloor \lvert x_i
      \rvert\rfloor
  
  
  Here, :math:`n` represents the number of dimensions and
  :math:`x_i \in [-5.12, 5.12]` for :math:`i = 1, ..., n`.
  
  *Global optimum*: :math:`f(x) = 30` for :math:`x_i = 0` for
  :math:`i = 1, ..., n`
  
  .. [1] Gavana, A. Global Optimization Benchmarks and AMPGO retrieved 2015
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code: def __init__(self, dimensions=2):
      Benchmark.__init__(self, dimensions)
  
      self._bounds = list(zip([-5.12] * self.N, [5.12] * self.N))
  
      self.global_optimum = [[0.0 for _ in range(self.N)]]
      self.fglob = 30.0
      self.change_dimensionality = True
  
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 Plateau object from inherited base classes: Benchmark with example: obj = Plateau(dimensions)