thursday/go_benchmark_functions/go_funcs_I.py

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# -*- coding: utf-8 -*-
from numpy import sin, sum
from .go_benchmark import Benchmark
class Infinity(Benchmark):
r"""
Infinity objective function.
This class defines the Infinity [1]_ global optimization problem. This
is a multimodal minimization problem defined as follows:
.. math::
f_{\text{Infinity}}(x) = \sum_{i=1}^{n} x_i^{6}
\left [ \sin\left ( \frac{1}{x_i} \right ) + 2 \right ]
Here, :math:`n` represents the number of dimensions and
:math:`x_i \in [-1, 1]` for :math:`i = 1, ..., n`.
*Global optimum*: :math:`f(x) = 0` for :math:`x_i = 0` for
:math:`i = 1, ..., n`
.. [1] Gavana, A. Global Optimization Benchmarks and AMPGO retrieved 2015
"""
def __init__(self, dimensions=2):
Benchmark.__init__(self, dimensions)
self._bounds = list(zip([-1.0] * self.N, [1.0] * self.N))
self.global_optimum = [[1e-16 for _ in range(self.N)]]
self.fglob = 0.0
self.change_dimensionality = True
def fun(self, x, *args):
self.nfev += 1
return sum(x ** 6.0 * (sin(1.0 / x) + 2.0))