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benchmark_functions.py
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import math
import numpy as np
#from scipy.interpolate import interp1d
from copy import deepcopy
def Currin(x, d):
return -1*float(((1 - math.exp(-0.5*(1/x[1]))) * ((2300*pow(x[0],3) + 1900*x[0]*x[0] + 2092*x[0] + 60)/(100*pow(x[0],3) + 500*x[0]*x[0] + 4*x[0] + 20))))
def branin(x1,d):
x=deepcopy(x1)
x[0]= 15* x[0]-5
x[1]=15*x[1]
return -1*float(np.square(x[1] - (5.1/(4*np.square(math.pi)))*np.square(x[0]) + (5/math.pi)*x[0]- 6) + 10*(1-(1./(8*math.pi)))*np.cos(x[0]) + 10)
def Powell(xx,d):
vmin=-4
vmax=5
x=[None]+list(vmin + np.asarray(xx) * (vmax-vmin))
f_original=0
for i in range(1,int(math.floor(d/4)+1)):
f_original=f_original+pow(x[4*i-3]+10*x[4*i-2],2)+5*pow(x[4*i-1]-x[4*i],2)+pow(x[4*i-2]-2*x[4*i-1],4)+10*pow(x[4*i-3]-2*x[4*i],4)
return -1*float(f_original)
def Perm(xx,d):
vmin=-1*d
vmax=d
beta=10
x=[None]+list(vmin + np.asarray(xx) * (vmax-vmin))
f_original=0
for i in range(1,d+1):
sum1=0
for j in range(1,d+1):
sum1=sum1+(j+beta)*(x[j]-math.pow(j,-1*i))
f_original=f_original+math.pow(sum1,2)
return -1*f_original
def Dixon(xx,d):
vmin=-10
vmax=10
x=[None]+list(vmin + np.asarray(xx) * (vmax-vmin))
f_original=0
for i in range(2,d+1):
f_original=f_original+i*math.pow(2*math.pow(x[i],2)-x[i-1],2)
f_original=f_original+math.pow(x[1]-1,1)
return -1*f_original
def ZAKHAROV(xx,d):
vmin=-5
vmax=10
x=[None]+list(vmin + np.asarray(xx) * (vmax-vmin))
term1=0
term2=0
for i in range(1,d+1):
term1=term1+x[i]**2
term2=term2+0.5*i*x[i]
f_original=term1+math.pow(term2,2)+math.pow(term2,4)
return -1*f_original
def RASTRIGIN(xx,d):
vmin=-5.12
vmax=5.12
x=[None]+list(vmin + np.asarray(xx) * (vmax-vmin))
f_original=0
for i in range(1,d+1):
f_original=f_original+(x[i]**2-10*math.cos(2*x[i]*math.pi))
f_original=f_original+10*d
return -1*f_original
def SumSquares(xx,d):
vmin=-5.12
vmax=5.12
x=[None]+list(vmin + np.asarray(xx) * (vmax-vmin))
f_original=0
for i in range(1,d+1):
f_original=f_original+(i*math.pow(x[i],2))
return -1*f_original
############################################
#d=3
def oka21(xx, d):
x=deepcopy(xx)
x[0]=x[0]*(2*3.14)-3.14
f_original = x[0]
return -1*f_original
def oka22(xx, d):
x=deepcopy(xx)
x[0]=x[0]*(2*3.14)-3.14
x[1]=x[1]*(2*5)-5
x[2]=x[2]*(2*5)-5
f_original=1-1./(4*pow(math.pi,2))*pow(x[0]+math.pi,2)+pow(np.abs(x[1]-5*math.cos(x[0])),1./3)+pow(np.abs(x[2]-5*math.sin(x[0])),1./3)
return -1*f_original
################################################
#d=5/d=3
def DTLZ14f_1(x, d):
g=0
for i in range(d):
g=g+pow(x[i]-0.5,2)-math.cos(20*math.pi*(x[i]-0.5))
g=100*(d+g)
y1=(1+g)*0.5*x[0]*x[1]*x[2]
return -1*y1
def DTLZ14f_2(x, d):
g=0
for i in range(d):
g=g+pow(x[i]-0.5,2)-math.cos(20*math.pi*(x[i]-0.5))
g=100*(d+g)
y2=(1+g)*0.5*(1-x[2])*x[0]*x[1]
return -1*y2
def DTLZ14f_3(x, d):
g=0
for i in range(d):
g=g+pow(x[i]-0.5,2)-math.cos(20*math.pi*(x[i]-0.5))
g=100*(d+g)
y3=(1+g)*0.5*(1-x[1])*x[0]
return -1*y3
def DTLZ14f_4(x, d):
g=0
for i in range(d):
g=g+pow(x[i]-0.5,2)-math.cos(20*math.pi*(x[i]-0.5))
g=100*(d+g)
y4=(1+g)*0.5*(1-x[0])
return -1*y4