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Jul 1, 20211 min

Python Implementation of Bohachevsky Function

Updated: Jul 18, 2021

Mathematical Definition

Input Domain

It can be defined on any input domain but it’s usually evaluated on the square 𝑥𝑖 ∈ [−100,100] for i=1,2

Global Minima

It has one local minima at 𝑓(𝑥 ∗ ) = 0 𝑎𝑡 𝑥 ∗ = (0,0).

Description and Features

Bohachevsky functions are continuous.

The function is defined on 2- dimensional space.

Bohachevsky functions are unimodal.

The functions all have the same similar bowl shape

Python Implementation

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import matplotlib.pyplot as plt
 
import numpy as np
 
from numpy import *
 
from numpy import cos
 
from numpy import pi
 
from numpy import abs,sqrt
 
from numpy import meshgrid
 
from mpl_toolkits.mplot3d import Axes3D
 

 
def f( x1,x2):
 
return x1**2 +2*(x2**2)-0.3*cos(3*pi*x1)-0.4*cos(4*pi*x2)+0.7
 

 
x1=np.linspace(-100,100,500)
 
x2=np.linspace(-100,100,500)
 
r_min,r_max=-100,100
 

 
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('Bohachevsky function')
 
axis.view_init(21,40)
 
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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