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Jul 4, 20211 min

Python implementation of McCormick Function

Updated: Aug 4, 2021

Mathematical Definition

Input Domain

The input range of the func is: x1∈ [-1.5, 4], x2∈ [-3, 4].

Global Minima

The func has one global min f(x*)=-1.9133, at x* = (0.54719,-1.54719)

Characteristics

The function is continuous.

The function is  convex.

The function is defined on 2-D space.

The function is multimodal.

The function is differentiable.

Python Implementation

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# Author: Dhanishtha Sharma
 

 
import sympy
 
import math
 
from sympy import symbols
 
from sympy import *
 
from sympy.plotting import plot3d
 
import numpy as np
 
import matplotlib as mpl
 
import matplotlib.pyplot as plt
 
from mpl_toolkits.mplot3d import Axes3D
 

 
%matplotlib notebook
 
plt.rcParams['figure.figsize'] = (6,4)
 
plt.rcParams['figure.dpi']=150
 
fig=plt.figure()
 
ax=fig.add_subplot(111,projection='3d')
 
x1,x2=symbols('x1 x2')
 
plot3d((sin(x1+x2)+(x1-x2)**2-1.5*x1+2.5*x2+1),(x1,-1.5,4,2),(x2,-3,4,2))
 

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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