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# encoding=utf8
# pylint: disable=anomalous-backslash-in-string
"""Implementation of Rosenbrock benchmark function.
Date: 2018
Authors: Iztok Fister Jr. and Lucija Brezočnik
License: MIT
Function: Rosenbrock function
Input domain:
The function can be defined on any input domain but it is usually
evaluated on the hypercube x_i ∈ [-30, 30], for all i = 1, 2,..., D.
Global minimum:
f(x*) = 0, at x* = (1,...,1)
LaTeX formats:
Inline: $f(x) = \sum_{i=1}^{D-1} (100 (x_{i+1} - x_i^2)^2 + (x_i - 1)^2)$
Equation: \begin{equation}
f(x) = \sum_{i=1}^{D-1} (100 (x_{i+1} - x_i^2)^2 + (x_i - 1)^2)
\end{equation}
Domain: $-30 \leq x_i \leq 30$
Reference paper:
Jamil, M., and Yang, X. S. (2013).
A literature survey of benchmark functions for global optimisation problems.
International Journal of Mathematical Modelling and Numerical Optimisation,
4(2), 150-194.
"""
import math
__all__ = ['Rosenbrock']
class Rosenbrock(object):
def __init__(self, Lower=-30, Upper=30):
self.Lower = Lower
self.Upper = Upper
@classmethod
def function(cls):
def evaluate(D, sol):
val = 0.0
for i in range(D - 1):
val += 100 * math.pow(sol[i + 1] - math.pow((sol[i]), 2), 2) + math.pow((sol[i] - 1), 2)
return val
return evaluate
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