class_docstr: Quintic objective function.
  
  This class defines the Quintic [1]_ global optimization problem. This is a
  multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Quintic}}(x) = \sum_{i=1}^{n} \left|{x_{i}^{5} - 3 x_{i}^{4}
      + 4 x_{i}^{3} + 2 x_{i}^{2} - 10 x_{i} -4}\right|
  
  
  Here, :math:`n` represents the number of dimensions and
  :math:`x_i \in [-10, 10]` for :math:`i = 1, ..., n`.
  
  *Global optimum*: :math:`f(x_i) = 0` 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([-10.0] * self.N, [10.0] * self.N))
      self.custom_bounds = [(-2, 2), (-2, 2)]
  
      self.global_optimum = [[-1.0 for _ in range(self.N)]]
      self.fglob = 0
      self.change_dimensionality = True
  
file_path: scipy/benchmarks/benchmarks/go_benchmark_functions/go_funcs_Q.py
imports: from numpy import abs, sum, arange, sqrt
  from .go_benchmark import Benchmark
label_desc: Use image node_id 1 to create a new Quintic object from inherited base classes: Benchmark with example: obj = Quintic(dimensions)