Source code for niapy.problems.powell

# encoding=utf8

"""Implementations of Powell function."""
import numpy as np

from niapy.problems.problem import Problem

__all__ = ['Powell']


[docs]class Powell(Problem): r"""Implementations of Powell functions. Date: 2018 Author: Klemen Berkovič License: MIT Function: **Powell Function** :math:`f(\textbf{x}) = \sum_{i = 1}^{D / 4} \left( (x_{4 i - 3} + 10 x_{4 i - 2})^2 + 5 (x_{4 i - 1} - x_{4 i})^2 + (x_{4 i - 2} - 2 x_{4 i - 1})^4 + 10 (x_{4 i - 3} - x_{4 i})^4 \right)` **Input domain:** The function can be defined on any input domain but it is usually evaluated on the hypercube :math:`x_i ∈ [-4, 5]`, for all :math:`i = 1, 2,..., D`. **Global minimum:** :math:`f(\textbf{x}^*) = 0` at :math:`\textbf{x}^* = (0, \cdots, 0)` LaTeX formats: Inline: $f(\textbf{x}) = \sum_{i = 1}^{D / 4} \left( (x_{4 i - 3} + 10 x_{4 i - 2})^2 + 5 (x_{4 i - 1} - x_{4 i})^2 + (x_{4 i - 2} - 2 x_{4 i - 1})^4 + 10 (x_{4 i - 3} - x_{4 i})^4 \right)$ Equation: \begin{equation} f(\textbf{x}) = \sum_{i = 1}^{D / 4} \left( (x_{4 i - 3} + 10 x_{4 i - 2})^2 + 5 (x_{4 i - 1} - x_{4 i})^2 + (x_{4 i - 2} - 2 x_{4 i - 1})^4 + 10 (x_{4 i - 3} - x_{4 i})^4 \right) \end{equation} Domain: $-4 \leq x_i \leq 5$ Reference: https://www.sfu.ca/~ssurjano/powell.html """
[docs] def __init__(self, dimension=4, lower=-4.0, upper=5.0, *args, **kwargs): r"""Initialize Powell problem.. Args: dimension (Optional[int]): Dimension of the problem. lower (Optional[Union[float, Iterable[float]]]): Lower bounds of the problem. upper (Optional[Union[float, Iterable[float]]]): Upper bounds of the problem. See Also: :func:`niapy.problems.Problem.__init__` """ super().__init__(dimension, lower, upper, *args, **kwargs)
[docs] @staticmethod def latex_code(): r"""Return the latex code of the problem. Returns: str: Latex code. """ return r'''$f(\textbf{x}) = \sum_{i = 1}^{D / 4} \left( (x_{4 i - 3} + 10 x_{4 i - 2})^2 + 5 (x_{4 i - 1} - x_{4 i})^2 + (x_{4 i - 2} - 2 x_{4 i - 1})^4 + 10 (x_{4 i - 3} - x_{4 i})^4 \right)$'''
def _evaluate(self, x): x1 = x[range(1, self.dimension - 3, 4)] x2 = x[range(2, self.dimension - 2, 4)] x3 = x[range(3, self.dimension - 1, 4)] x4 = x[range(4, self.dimension, 4)] term1 = (x1 + 10 * x2) ** 2.0 term2 = 5 * (x3 - x4) ** 2.0 term3 = (x2 - 2 * x3) ** 4.0 term4 = 10 * (x1 - x4) ** 4.0 return np.sum(term1 + term2 + term3 + term4)