class_docstr: Tripod objective function.
  
  This class defines the Tripod [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Tripod}}(x) = p(x_2) \left[1 + p(x_1) \right] +
                             \lvert x_1 + 50p(x_2) \left[1 - 2p(x_1) \right]
                             \rvert + \lvert x_2 + 50\left[1 - 2p(x_2)\right]
                             \rvert
  
  with :math:`x_i \in [-100, 100]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x = [0, -50]`
  
  .. [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([-100.0] * self.N, [100.0] * self.N))
  
      self.global_optimum = [[0.0, -50.0]]
      self.fglob = 0.0
  
imports: from numpy import abs, asarray, cos, exp, arange, pi, sin, sum, atleast_2d
  from .go_benchmark import Benchmark
label_desc: Use image node_id 1 to create a new Tripod object from inherited base classes: Benchmark with example: obj = Tripod(dimensions)