Question

Program a Genetic Algorithm to find an integer number between 0 and 31 that minimizes the function ?(?) = (? − 10) . Design your program with the necessary parameters.

Answer 1

Output

Code in python

import numpy as np

class Genetic(object):

def __init__(self, f, pop_size = 100, n_variables = 2):
self.f = f
self.minim = 0
self.maxim = 31
self.pop_size = pop_size
self.n_variables = n_variables
self.population = self.initializePopulation()
self.evaluatePopulation()

def initializePopulation(self):
return [np.random.randint(self.minim, self.maxim, size=(self.n_variables))
for i in range(self.pop_size)]

def evaluatePopulation(self):
return [self.f(i[0], i[1]) for i in self.population]
#return [(i[0]-4)**2 + i[1]**2 for i in self.population]

def nextGen(self):
results = self.evaluatePopulation()
children = [self.population[np.argmin(results)]]

while len(children) < self.pop_size:
# Tournament selection
randA, randB = np.random.randint(0, self.pop_size), \
np.random.randint(0, self.pop_size)
if results[randA] < results[randB]: p1 = self.population[randA]
else: p1 = self.population[randB]

randA, randB = np.random.randint(0, self.pop_size), \
np.random.randint(0, self.pop_size)
if results[randA] < results[randB]: p2 = self.population[randA]
else: p2 = self.population[randB]   

signs = []
for i in zip(p1, p2):
if i[0] < 0 and i[1] < 0: signs.append(-1)
elif i[0] >= 0 and i[1] >= 0: signs.append(1)
else: signs.append(np.random.choice([-1,1]))

# Convert values to binary
p1 = [format(abs(i), '010b') for i in p1]
p2 = [format(abs(i), '010b') for i in p2]

# Recombination
child = []
for i, j in zip(p1, p2):
for k, l in zip(i, j):
if k == l: child.append(k)
else: child.append(str(np.random.randint(min(k, l),
max(k,l))))

child = ''.join(child)
g1 = child[0:len(child)//2]
g2 = child[len(child)//2:len(child)]
children.append(np.asarray([signs[0]*int(g1, 2),
signs[1]*int(g2, 2)]))
self.population = children

def run(self):
ix = 0
while ix < 1000:
ix += 1
self.nextGen()
return self.population[0]

f = lambda x, y: (x-10) + y**2
gen = Genetic(f)
minim = gen.run()
print('Minimum found X =', minim[0], ', Y =', minim[1])