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Jul 1, 20211 min

Python Implementation of Perm 0,d beta Function

Updated: Jul 18, 2021

Mathematical Definition

Input Domain

It can be defined into any input domain but usually perm 0, d, beta function evaluated on the hypercube 𝑥𝑖 𝜖 [−𝑑, 𝑑], for all 𝑖 = 1, … . , 𝑑.

Global Minima

The function has one global minimum 𝑓(𝑥 ∗) = 0, 𝑎𝑡 𝑥 ∗ = (1, 1 /2 , … , 1 /𝑑 )

Description and Features

The function is defined on 2- dimensional space

Python Implementation

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import matplotlib.pyplot as plt
 
import numpy as np
 
from numpy import sin
 

 
from numpy import e
 
from numpy import meshgrid
 
from mpl_toolkits.mplot3d import Axes3D
 
from matplotlib import cm
 

 
def f(x1,x2):
 

 
return (11*(x1-1)+12*(x2-0.5))**2 + (11*(x1**2-1)+12*(x2**2-0.25))**2
 

 
x1=np.linspace(-2,2)
 
x2=np.linspace(-2,2)
 
r_min,r_max=1,2
 

 
x1,x2=np.meshgrid(x1,x2)
 
results=f(x1,x2)
 

 
figure=plt.figure(figsize=(9,9))
 
axis=figure.gca(projection='3d')
 
axis.contour3D(x1, x2, results,450)
 
axis.set_title('Perm function 0,d,beta')
 
axis.view_init(40,40)
 
axis.set_xlabel('X')
 
axis.set_ylabel('Y')
 
axis.set_zlabel('Z')
 
plt.show()

References:

[1] Jamil, Momin, and Xin-She Yang. "A literature survey of benchmark functions for global optimization problems." International Journal of Mathematical Modelling and Numerical Optimization 4.2 (2013): 150-194.

#optimization #benchmarkfunction

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