# your code goes here
from math import *
from random import *
from time import *
cst = float ( 'inf' )
global x, y, X, r1, worst, lam
global g, geq, gen
global vals
global f, f_new, T, O1, O2
def getH( g) :
if g <= 0 :
return 0
else :
return 1
def getHeq( geq) :
if geq == 0 :
return 0
else :
return 1
def ineq( x) :
g = [ 0 ]
#g1 = x[1]+5
#g.append(g1)
return g
def eq( x) :
geq = [ 0 ]
#geq1 = x[1]+5
#geq.append(geq1)
return geq
def fobj( x) :
for i in range ( var+1 ) :
if x[ i] > 0 :
y[ i] = 1
else :
y[ i] = 0
#print("x =",x)
#print("y =",y)
Z = abs ( x[ 1 ] ) +abs ( x[ 2 ] ) +abs ( x[ 3 ] ) +abs ( x[ 4 ] ) +abs ( x[ 5 ] ) +abs ( x[ 6 ] ) +abs ( x[ 7 ] ) +abs ( x[ 8 ] ) +abs ( x[ 9 ] ) +abs ( x[ 10 ] ) +abs ( x[ 1 ] ) *abs ( x[ 2 ] ) *abs ( x[ 3 ] ) *abs ( x[ 4 ] ) *abs ( x[ 5 ] ) *abs ( x[ 6 ] ) *abs ( x[ 7 ] ) *abs ( x[ 8 ] ) *abs ( x[ 9 ] ) *abs ( x[ 10 ] )
g = ineq( x)
geq = eq( x)
for k in range ( 1 , len ( g) ) :
Z = Z+lam*( g[ k] **2 ) *getH( g[ k] )
for k in range ( 1 , len ( geq) ) :
Z = Z+lam*( geq[ k] **2 ) *getHeq( geq[ k] )
return Z
pop = 30
var = 10
maxGen = 4500
mini = [ 0 , -5 , -5 , -5 , -5 , -5 , -5 , -5 , -5 , -5 , -5 ]
#maxi = [0, 1, 1, 3, 1, 45, 1, 35, 1, 92, 1, 93, 40, 55, 1, 1, 1, 1, 61, 60, 1, 1, 25, 40, 93, 1, 1, 1, 1, 3, 3, 95, 93, 3, 95, 96, 90, 3, 3, 40, 95, 50, 3, 3, 37, 3, 3, 35, 70, 93, 45]
maxi = [ 0 , 5 , 5 , 5 , 5 , 5 , 5 , 5 , 5 , 5 , 5 ]
#maxi = [0, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30]
#lam = 7
O1 = 1.00000000027
O2 = 1.0000957
g = [ ]
geq = [ ]
x = [ 0 for i in range ( var+1 ) ]
X = [ [ 0 for i in range ( var+1 ) ] for j in range ( pop+1 ) ]
M = [ [ 0 for i in range ( var+1 ) ] for j in range ( pop+1 ) ]
y = [ 0 for i in range ( var+1 ) ]
f = [ 0 for i in range ( pop+1 ) ]
f[ 0 ] = cst
for j in range ( 1 , var+1 ) :
for i in range ( 1 , pop+1 ) :
X[ i] [ j] = mini[ j] +( maxi[ j] -mini[ j] ) *random ( )
M[ i] [ j] = X[ i] [ j]
def method_1( ) :
global r1, worst
if gen == 1 :
for i in range ( 1 , pop+1 ) :
f[ i] = fobj( X[ i] )
if i == 1 :
best = i
worst = i
else :
if f[ best] > f[ i] :
best = i
if f[ worst] < f[ i] :
worst = i
r1 = best
X_best = X[ best]
X_worst = X[ worst]
else :
for i in range ( 1 , pop+1 ) :
if i == 1 :
best = i
worst = i
else :
if f[ best] > f[ i] :
best = i
if f[ worst] < f[ i] :
worst = i
X_best = X[ best]
X_worst = X[ worst]
X_t = [ [ 0 for i in range ( var+1 ) ] for j in range ( pop+1 ) ]
for i in range ( 1 , pop+1 ) :
for j in range ( 1 , var+1 ) :
X_t[ i] [ j] = X[ i] [ j]
for i in range ( 1 , pop+1 ) :
for j in range ( 1 , var+1 ) :
vals = X[ i] [ j] +random ( ) *( X_best[ j] -abs ( X[ i] [ j] ) ) -random ( ) *( X_worst[ j] -abs ( X[ i] [ j] ) )
if vals < mini[ j] :
X_t[ i] [ j] = mini[ j]
elif vals > maxi[ j] :
X_t[ i] [ j] = maxi[ j]
else :
X_t[ i] [ j] = vals
f_new = [ 0 ]
for i in range ( 1 , pop+1 ) :
f_new.append ( fobj( X_t[ i] ) )
for i in range ( 1 , pop+1 ) :
if f[ i] > f_new[ i] :
X[ i] = X_t[ i]
f[ i] = f_new[ i]
if i == 1 :
worst = i
elif f[ worst] < f[ i] :
worst = i
def method_2( ) :
p = [ i for i in range ( 1 , pop+1 ) ]
p.remove ( r1)
r2 = choice( p)
p.remove ( r2)
r3 = choice( p)
ex = 0
X_child = [ 0 ]
for i in range ( 1 , var+1 ) :
R1 = X[ r1] [ i]
R2 = X[ r2] [ i]
R3 = X[ r3] [ i]
fR1 = fobj( X[ r1] )
fR2 = fobj( X[ r2] )
fR3 = fobj( X[ r3] )
den = ( R2-R3) *fR1+( R3-R1) *fR2+( R1-R2) *fR3
tries = 0
while den == 0 :
tries += 1
if tries > 10 :
ex = 1
break
r3 = choice( p)
R3 = X[ r3] [ i]
fR3 = fobj( X[ r3] )
den = ( R2-R3) *fR1+( R3-R1) *fR2+( R1-R2) *fR3
if ex == 1 :
break
val = 0.5 *( float ( ( R2**2 -R3**2 ) *fR1+( R3**2 -R1**2 ) *fR2+( R1**2 -R2**2 ) *fR3) /( ( R2-R3) *fR1+( R3-R1) *fR2+( R1-R2) *fR3) )
if val < mini[ j] :
X_child.append ( mini[ j] )
elif val > maxi[ j] :
X_child.append ( maxi[ j] )
else :
X_child.append ( val)
if ex == 0 :
f_child = fobj( X_child)
if f_child < f[ worst] :
f[ worst] = f_child
X[ worst] = X_child
def sol( ) :
print ( "\n Solution table:\n " )
s = ""
for i in range ( 1 , var+1 ) :
s += "x" +str ( i) +" "
print ( s+"f(x)\n " )
for i in range ( 1 , pop+1 ) :
s = ""
for j in range ( 1 , var+1 ) :
s += str ( X[ i] [ j] ) +" "
print ( s+" " +str ( f[ i] ) +"\n " )
gen = 1
T = float ( 'inf' )
final = 1
start_time = time ( )
while gen <= maxGen:
p = ( O2 - O1) /( 1 + e**( ( 20 *( -gen+( maxGen/4 ) ) ) /maxGen) ) + O1
lam = 10 **p
method_1( )
if T >= min ( f) :
T = min ( T, min ( f) )
for i in range ( 1 , pop+1 ) :
if f[ i] == T:
vals = X[ i]
break
final = f.index ( min ( f) )
T = min ( T, min ( f) )
#print("Gen "+str(gen)+":",T)
gen += 1
#sol()
'''final = 1
for i in range (1, pop+1):
if f[final] > f[i]:
final = i
'''
#sol()
execution_time = time ( ) -start_time
print ( "Execution time in seconds: " +str ( execution_time) )
print ( "Final solution:\n " )
print ( "Values:" )
for i in range ( 1 , var+1 ) :
print ( "x" +str ( i) +" = " +str ( X[ final] [ i] ) )
x = X[ final]
for i in range ( var+1 ) :
if x[ i] > 0 :
y[ i] = 1
else :
y[ i] = 0
#Enter equation here
Z = abs ( x[ 1 ] ) +abs ( x[ 2 ] ) +abs ( x[ 3 ] ) +abs ( x[ 4 ] ) +abs ( x[ 5 ] ) +abs ( x[ 6 ] ) +abs ( x[ 7 ] ) +abs ( x[ 8 ] ) +abs ( x[ 9 ] ) +abs ( x[ 10 ] ) +abs ( x[ 1 ] ) *abs ( x[ 2 ] ) *abs ( x[ 3 ] ) *abs ( x[ 4 ] ) *abs ( x[ 5 ] ) *abs ( x[ 6 ] ) *abs ( x[ 7 ] ) *abs ( x[ 8 ] ) *abs ( x[ 9 ] ) *abs ( x[ 10 ] )
#print("\nf(x) = "+str(T))
print ( "\n f(x) = " +str ( Z) )
x = vals
print ( "\n Final solution:\n " )
print ( "Values:" )
for i in range ( 1 , var+1 ) :
print ( "x" +str ( i) +" = " +str ( vals[ i] ) )
#x = X[final]
for i in range ( var+1 ) :
if x[ i] > 0 :
y[ i] = 1
else :
y[ i] = 0
Z = abs ( x[ 1 ] ) +abs ( x[ 2 ] ) +abs ( x[ 3 ] ) +abs ( x[ 4 ] ) +abs ( x[ 5 ] ) +abs ( x[ 6 ] ) +abs ( x[ 7 ] ) +abs ( x[ 8 ] ) +abs ( x[ 9 ] ) +abs ( x[ 10 ] ) +abs ( x[ 1 ] ) *abs ( x[ 2 ] ) *abs ( x[ 3 ] ) *abs ( x[ 4 ] ) *abs ( x[ 5 ] ) *abs ( x[ 6 ] ) *abs ( x[ 7 ] ) *abs ( x[ 8 ] ) *abs ( x[ 9 ] ) *abs ( x[ 10 ] )
#print("\nf(x) = "+str(T))
print ( "\n f(x) = " +str ( Z) )
#print()
#print()
#print(ineq(X[final]))
#print(g)
print ( )
print ( )
for j in range ( 1 , var+1 ) :
for i in range ( 1 , pop+1 ) :
X[ i] [ j] = M[ i] [ j]
gen = 1
T = float ( 'inf' )
final = 1
start_time = time ( )
while gen <= maxGen:
p = ( ( O2 - O1) /( 1 + e**( ( 20 *( -gen+( maxGen/4 ) ) ) /maxGen) ) ) + O1
lam = 10 **p
if gen % 2 == 1 :
method_1( )
else :
method_2( )
if T >= min ( f) :
T = min ( T, min ( f) )
for i in range ( 1 , pop+1 ) :
if f[ i] == T:
vals = X[ i]
break
final = f.index ( min ( f) )
T = min ( T, min ( f) )
#print("Gen "+str(gen)+":",T)
gen += 1
#sol()
'''final = 1
for i in range (1, pop+1):
if f[final] > f[i]:
final = i
'''
#sol()
execution_time = time ( ) -start_time
print ( "Execution time in seconds: " +str ( execution_time) )
print ( "Final solution:\n " )
print ( "Values:" )
for i in range ( 1 , var+1 ) :
print ( "x" +str ( i) +" = " +str ( X[ final] [ i] ) )
x = X[ final]
for i in range ( var+1 ) :
if x[ i] > 0 :
y[ i] = 1
else :
y[ i] = 0
#Enter equation here
Z = abs ( x[ 1 ] ) +abs ( x[ 2 ] ) +abs ( x[ 3 ] ) +abs ( x[ 4 ] ) +abs ( x[ 5 ] ) +abs ( x[ 6 ] ) +abs ( x[ 7 ] ) +abs ( x[ 8 ] ) +abs ( x[ 9 ] ) +abs ( x[ 10 ] ) +abs ( x[ 1 ] ) *abs ( x[ 2 ] ) *abs ( x[ 3 ] ) *abs ( x[ 4 ] ) *abs ( x[ 5 ] ) *abs ( x[ 6 ] ) *abs ( x[ 7 ] ) *abs ( x[ 8 ] ) *abs ( x[ 9 ] ) *abs ( x[ 10 ] )
#print("\nf(x) = "+str(T))
print ( "\n f(x) = " +str ( Z) )
#print(ineq(X[final]))
#print(g)
x = vals
print ( "\n Final solution:\n " )
print ( "Values:" )
for i in range ( 1 , var+1 ) :
print ( "x" +str ( i) +" = " +str ( vals[ i] ) )
#x = X[final]
for i in range ( var+1 ) :
if x[ i] > 0 :
y[ i] = 1
else :
y[ i] = 0
Z = abs ( x[ 1 ] ) +abs ( x[ 2 ] ) +abs ( x[ 3 ] ) +abs ( x[ 4 ] ) +abs ( x[ 5 ] ) +abs ( x[ 6 ] ) +abs ( x[ 7 ] ) +abs ( x[ 8 ] ) +abs ( x[ 9 ] ) +abs ( x[ 10 ] ) +abs ( x[ 1 ] ) *abs ( x[ 2 ] ) *abs ( x[ 3 ] ) *abs ( x[ 4 ] ) *abs ( x[ 5 ] ) *abs ( x[ 6 ] ) *abs ( x[ 7 ] ) *abs ( x[ 8 ] ) *abs ( x[ 9 ] ) *abs ( x[ 10 ] )
#print("\nf(x) = "+str(T))
print ( "\n f(x) = " +str ( Z) )

# your code goes here
from math import *
from random import *
from time import *

cst = float('inf')
global x, y, X, r1, worst, lam
global g, geq, gen
global vals
global f, f_new, T, O1, O2

def getH(g):
    if g <= 0:
        return 0
    else:
        return 1

def getHeq(geq):
    if geq == 0:
        return 0
    else:
        return 1
   
def ineq(x):
    g = [0]
   
    #g1 = x[1]+5
    #g.append(g1)

   
    
    
   
    return g

def eq(x):
    geq = [0]
   
    #geq1 = x[1]+5
    #geq.append(geq1)

    return geq

def fobj(x):
    for i in range (var+1):
        if x[i] > 0:
            y[i] = 1
        else:
            y[i] = 0

    #print("x =",x)
    #print("y =",y)
   
    Z = abs(x[1])+abs(x[2])+abs(x[3])+abs(x[4])+abs(x[5])+abs(x[6])+abs(x[7])+abs(x[8])+abs(x[9])+abs(x[10])+abs(x[1])*abs(x[2])*abs(x[3])*abs(x[4])*abs(x[5])*abs(x[6])*abs(x[7])*abs(x[8])*abs(x[9])*abs(x[10])

    g = ineq(x)
    geq = eq(x)

    for k in range (1, len(g)):
        Z = Z+lam*(g[k]**2)*getH(g[k])
       
    for k in range (1, len(geq)):
        Z = Z+lam*(geq[k]**2)*getHeq(geq[k])
       
    return Z

pop = 30
var = 10
maxGen = 4500
mini =[0, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5]
#maxi = [0, 1, 1, 3, 1, 45, 1, 35, 1, 92, 1, 93, 40, 55, 1, 1, 1, 1, 61, 60, 1, 1, 25, 40, 93, 1, 1, 1, 1, 3, 3, 95, 93, 3, 95, 96, 90, 3, 3, 40, 95, 50, 3, 3, 37, 3, 3, 35, 70, 93, 45]
maxi = [0, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5]
#maxi = [0, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30]
#lam = 7
O1 = 1.00000000027
O2 = 1.0000957

g = []
geq = []

x = [0 for i in range (var+1)]
X = [[0 for i in range (var+1)] for j in range (pop+1)]
M = [[0 for i in range (var+1)] for j in range (pop+1)]

y = [0 for i in range (var+1)]

f = [0 for i in range (pop+1)]
f[0] = cst

for j in range (1, var+1):
    for i in range (1, pop+1):
        X[i][j] = mini[j]+(maxi[j]-mini[j])*random()
        M[i][j] = X[i][j]

def method_1():
    global r1, worst
   
    if gen == 1:
        for i in range (1, pop+1):
            f[i] = fobj(X[i])
            if i == 1:
                best = i
                worst = i
            else:
                if f[best] > f[i]:
                    best = i
                if f[worst] < f[i]:
                    worst = i

        r1 = best
        X_best = X[best]
        X_worst = X[worst]

    else:
        for i in range (1, pop+1):
            if i == 1:
                best = i
                worst = i
            else:
                if f[best] > f[i]:
                    best = i
                if f[worst] < f[i]:
                    worst = i

        X_best = X[best]
        X_worst = X[worst]


    X_t = [[0 for i in range (var+1)] for j in range (pop+1)]

    for i in range(1, pop+1):
        for j in range (1, var+1):
            X_t[i][j] = X[i][j]
   
    for i in range (1, pop+1):
        for j in range (1, var+1):
            vals = X[i][j]+random()*(X_best[j]-abs(X[i][j]))-random()*(X_worst[j]-abs(X[i][j]))
            if vals < mini[j]:
                X_t[i][j] = mini[j]
            elif vals > maxi[j]:
                X_t[i][j] = maxi[j]
            else:
                X_t[i][j] = vals

    f_new = [0]
    for i in range (1, pop+1):
        f_new.append(fobj(X_t[i]))

    for i in range (1, pop+1):
        if f[i] > f_new[i]:
            X[i] = X_t[i]
        f[i] = f_new[i]
       
        if i == 1:
            worst = i
        elif f[worst] < f[i]:
            worst = i

def method_2():
    p = [i for i in range (1, pop+1)]
    p.remove(r1)

    r2 = choice(p)
    p.remove(r2)
    r3 = choice(p)
    ex = 0
   
    X_child = [0]

    for i in range (1, var+1):
        R1 = X[r1][i]
        R2 = X[r2][i]
        R3 = X[r3][i]

        fR1 = fobj(X[r1])
        fR2 = fobj(X[r2])
        fR3 = fobj(X[r3])

        den = (R2-R3)*fR1+(R3-R1)*fR2+(R1-R2)*fR3
        tries = 0
        while den == 0:
            tries += 1
            if tries > 10:
                ex = 1
                break
            r3 = choice(p)
            R3 = X[r3][i]
            fR3 = fobj(X[r3])
            den = (R2-R3)*fR1+(R3-R1)*fR2+(R1-R2)*fR3

        if ex == 1:
            break
        val = 0.5*(float((R2**2-R3**2)*fR1+(R3**2-R1**2)*fR2+(R1**2-R2**2)*fR3)/((R2-R3)*fR1+(R3-R1)*fR2+(R1-R2)*fR3))
        if val < mini[j]:
            X_child.append(mini[j])
        elif val > maxi[j]:
            X_child.append(maxi[j])
        else:
            X_child.append(val)

    if ex == 0:
        f_child = fobj(X_child)

        if f_child < f[worst]:
            f[worst] = f_child
            X[worst] = X_child

def sol():
    print("\nSolution table:\n")
    s = ""
    for i in range (1, var+1):
        s += "x"+str(i)+" "
    print(s+"f(x)\n")
   
    for i in range (1, pop+1):
        s = ""
        for j in range (1, var+1):
            s += str(X[i][j])+" "
        print(s+" "+str(f[i])+"\n")
   
gen = 1
T = float('inf')
final = 1

start_time = time()

while gen <= maxGen:
    p = (O2 - O1)/(1 + e**((20*(-gen+(maxGen/4)))/maxGen)) + O1
    lam = 10**p
   
    method_1()

    if T >= min(f):
        T = min(T, min(f))
        for i in range (1, pop+1):
            if f[i] == T:
                vals = X[i]
                break
        final = f.index(min(f))
       
    T = min(T, min(f))

    #print("Gen "+str(gen)+":",T)
   
    gen += 1
    #sol()

'''final = 1
for i in range (1, pop+1):
    if f[final] > f[i]:
        final = i
'''

#sol()

execution_time = time()-start_time
print("Execution time in seconds: "+str(execution_time))

print("Final solution:\n")
print("Values:")
for i in range (1, var+1):
    print("x"+str(i)+" = "+str(X[final][i]))

x = X[final]
for i in range (var+1):
    if x[i] > 0:
        y[i] = 1
    else:
        y[i] = 0

#Enter equation here
Z = abs(x[1])+abs(x[2])+abs(x[3])+abs(x[4])+abs(x[5])+abs(x[6])+abs(x[7])+abs(x[8])+abs(x[9])+abs(x[10])+abs(x[1])*abs(x[2])*abs(x[3])*abs(x[4])*abs(x[5])*abs(x[6])*abs(x[7])*abs(x[8])*abs(x[9])*abs(x[10])

#print("\nf(x) = "+str(T))
print("\nf(x) = "+str(Z))



x = vals
print("\nFinal solution:\n")
print("Values:")
for i in range (1, var+1):
    print("x"+str(i)+" = "+str(vals[i]))

#x = X[final]
for i in range (var+1):
    if x[i] > 0:
        y[i] = 1
    else:
        y[i] = 0

Z = abs(x[1])+abs(x[2])+abs(x[3])+abs(x[4])+abs(x[5])+abs(x[6])+abs(x[7])+abs(x[8])+abs(x[9])+abs(x[10])+abs(x[1])*abs(x[2])*abs(x[3])*abs(x[4])*abs(x[5])*abs(x[6])*abs(x[7])*abs(x[8])*abs(x[9])*abs(x[10])

#print("\nf(x) = "+str(T))
print("\nf(x) = "+str(Z))



#print()
#print()

#print(ineq(X[final]))
#print(g)


print()
print()

for j in range (1, var+1):
    for i in range (1, pop+1):
        X[i][j] = M[i][j]

gen = 1
T = float('inf')
final = 1

start_time = time()

while gen <= maxGen:
    p = ((O2 - O1)/(1 + e**((20*(-gen+(maxGen/4)))/maxGen))) + O1
    lam = 10**p
   
    if gen % 2 == 1:
        method_1()
    else:
        method_2()

    if T >= min(f):
        T = min(T, min(f))
        for i in range (1, pop+1):
            if f[i] == T:
                vals = X[i]
                break
        final = f.index(min(f))
       
    T = min(T, min(f))

    #print("Gen "+str(gen)+":",T)
   
    gen += 1
    #sol()

'''final = 1
for i in range (1, pop+1):
    if f[final] > f[i]:
        final = i
'''

#sol()

execution_time = time()-start_time
print("Execution time in seconds: "+str(execution_time))

print("Final solution:\n")
print("Values:")
for i in range (1, var+1):
    print("x"+str(i)+" = "+str(X[final][i]))

x = X[final]
for i in range (var+1):
    if x[i] > 0:
        y[i] = 1
    else:
        y[i] = 0

#Enter equation here
Z = abs(x[1])+abs(x[2])+abs(x[3])+abs(x[4])+abs(x[5])+abs(x[6])+abs(x[7])+abs(x[8])+abs(x[9])+abs(x[10])+abs(x[1])*abs(x[2])*abs(x[3])*abs(x[4])*abs(x[5])*abs(x[6])*abs(x[7])*abs(x[8])*abs(x[9])*abs(x[10])

#print("\nf(x) = "+str(T))
print("\nf(x) = "+str(Z))

#print(ineq(X[final]))
#print(g)



x = vals
print("\nFinal solution:\n")
print("Values:")
for i in range (1, var+1):
    print("x"+str(i)+" = "+str(vals[i]))

#x = X[final]
for i in range (var+1):
    if x[i] > 0:
        y[i] = 1
    else:
        y[i] = 0

Z = abs(x[1])+abs(x[2])+abs(x[3])+abs(x[4])+abs(x[5])+abs(x[6])+abs(x[7])+abs(x[8])+abs(x[9])+abs(x[10])+abs(x[1])*abs(x[2])*abs(x[3])*abs(x[4])*abs(x[5])*abs(x[6])*abs(x[7])*abs(x[8])*abs(x[9])*abs(x[10])
#print("\nf(x) = "+str(T))
print("\nf(x) = "+str(Z))
