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cuckooSearchOnCon2.py
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cuckooSearchOnCon2.py
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import math
import numpy as np
import random
import timeit
import matplotlib.pyplot as plt
class CS :
def __init__(self, nestCount, pa, stepSize, ranges):
self.nestCount = nestCount # count of nests
self.pa = pa # Probability of discovered
self.generation = 0 # current generation
self.nests = [] # nests set
self.fitness = [] # fitness set
self.stepSize = stepSize # step size 'a'
self.ranges = [ranges*-1, ranges] # problem ranges
self.population = [] # [nests, fitness] set
def ackleyFunc(self, x, y):
# optimal point == min(0, 0) = 0
z = -20 * math.exp(math.fabs(-0.2 * math.sqrt(0.5 * (x ** 2 + y ** 2)))) - math.exp(
math.fabs(0.5 * (math.cos(2 * x * math.pi) + math.cos(2 * y * math.pi)))) + math.e + 20
return math.fabs(z)
def levyFlight(self):
# u의 세제곱근분의 1
return math.pow(random.uniform(0.0001, 0.9999), -1.0 / 3.0)
def visualize(self):
data = self.population[:, 0].copy()
x = []
y = []
for i in range(len(self.population)) :
x.append(data[i][0])
y.append(data[i][1])
plt.plot(x, y, 'ro')
plt.axis([self.ranges[0], self.ranges[1], self.ranges[0], self.ranges[1]])
plt.show()
def search(self):
# Init nests
for i in range(self.nestCount):
X = round(random.uniform(self.ranges[0], self.ranges[1]), 6)
Y = round(random.uniform(self.ranges[0], self.ranges[1]), 6)
self.fitness.append(round(self.ackleyFunc(X, Y),4))
self.nests.append(np.array([X, Y]))
self.population = np.array([self.nests, self.fitness])
self.population = self.population.T # transpose matrix
self.population = self.population[np.argsort(self.population[:, 1])] # sorting
print('초기화 최대 해 : \n', self.population[0, 0], "\n", self.population[0, 1])
self.visualize()
while self.generation < 10000:
self.generation += 1
# Get a cuckoo randomly by levy flight
cuckooNest = self.population[random.randint(0, self.nestCount - 1), 0]
levyX = self.levyFlight()
levyY = self.levyFlight()
cuckooNest = np.array([round(cuckooNest[0]+self.stepSize*levyX, 6), round(cuckooNest[1]+self.stepSize*levyY, 6)])
randomNestIndex = random.randint(0, self.nestCount - 1)
# Evaluate and replace
if (self.population[randomNestIndex, 1] > self.ackleyFunc(cuckooNest[0], cuckooNest[1])):
self.population[randomNestIndex, 0] = cuckooNest
self.population[randomNestIndex, 1] = self.ackleyFunc(cuckooNest[0], cuckooNest[1])
# Pa of worse nests are abandoned and new ones built
for i in range(self.nestCount - int(self.pa * self.nestCount), self.nestCount):
X = round(random.uniform(self.ranges[0], self.ranges[1]), 6)
Y = round(random.uniform(self.ranges[0], self.ranges[1]), 6)
self.population[i, 0] = np.array([X, Y])
self.population[i, 1] = round(self.ackleyFunc(X, Y), 4)
self.population = self.population[np.argsort(self.population[:, 1])]
if self.generation % 500 == 0:
print(self.generation, '세대 최적 해 : \n', self.population[0, 1])
print(self.population[0, 0])
print(self.population)
self.visualize()
if __name__ == "__main__" :
cs = CS(100, 0.25, 1, 5)
start = timeit.default_timer()
cs.search()
stop = timeit.default_timer()
print(stop - start)