Source code for NiaPy.benchmarks.happyCat

# encoding=utf8
# pylint: disable=anomalous-backslash-in-string
import math

__all__ = ['HappyCat']


[docs]class HappyCat(object): r"""Implementation of Happy cat function. Date: 2018 Author: Lucija Brezočnik License: MIT Function: **Happy cat function** :math:`f(\mathbf{x}) = {\left |\sum_{i = 1}^D {x_i}^2 - D \right|}^{1/4} + (0.5 \sum_{i = 1}^D {x_i}^2 + \sum_{i = 1}^D x_i) / D + 0.5` **Input domain:** The function can be defined on any input domain but it is usually evaluated on the hypercube :math:`x_i ∈ [-100, 100]`, for all :math:`i = 1, 2,..., D`. **Global minimum:** :math:`f(x^*) = 0`, at :math:`x^* = (-1,...,-1)` LaTeX formats: Inline: $f(\mathbf{x}) = {\left|\sum_{i = 1}^D {x_i}^2 - D \right|}^{1/4} + (0.5 \sum_{i = 1}^D {x_i}^2 + \sum_{i = 1}^D x_i) / D + 0.5$ Equation: \begin{equation} f(\mathbf{x}) = {\left| \sum_{i = 1}^D {x_i}^2 - D \right|}^{1/4} + (0.5 \sum_{i = 1}^D {x_i}^2 + \sum_{i = 1}^D x_i) / D + 0.5 \end{equation} Domain: $-100 \leq x_i \leq 100$ Reference: http://bee22.com/manual/tf_images/Liang%20CEC2014.pdf """ def __init__(self, Lower=-100.0, Upper=100.0): self.Lower = Lower self.Upper = Upper
[docs] @classmethod def function(cls): def evaluate(D, sol): val1 = 0.0 val2 = 0.0 alpha = 0.125 for i in range(D): val1 += math.pow(abs(math.pow(sol[i], 2) - D), alpha) val2 += (0.5 * math.pow(sol[i], 2) + sol[i]) / D return val1 + val2 + 0.5
return evaluate