def linear_crossover(genome_1: Genome, genome_2: Genome) -> Genome:
a: float = rd.uniform(0, 1)
new_genes = (genome_1.genes * a + (1 - a) * genome_2.genes)
for i in range(len(new_genes)):
new_genes[i] = round(new_genes[i], 0)
return Genome(new_genes)
def multi_point_crossover(genome_1: Genome, genome_2: Genome) -> Genome:
num_of_points = randint(0, const.GENOME_LENGTH)
selection = rd.choices([0, 1], weights=[5, 5], k=1)
new_genes = []
multi_points = []
for i in range(num_of_points):
multi_points.append(randint(0, const.GENOME_LENGTH))
# remove duplicate variables from the list
multi_points = list(dict.fromkeys(multi_points))
multi_points.sort()
counter = 0
if selection[0] == 0:
for i in range(const.GENOME_LENGTH):
if i >= multi_points[counter]:
counter += 1
if counter % 2 == 0:
new_genes.append(genome_1.genes[i])
else:
new_genes.append(genome_2.genes[i])
else:
for i in range(const.GENOME_LENGTH):
if i >= multi_points[counter]:
counter += 1
if counter % 2 == 0:
new_genes.append(genome_2.genes[i])
else:
new_genes.append(genome_1.genes[i])
return Genome(new_genes)
def uniform_crossover(genome_1: Genome, genome_2: Genome) -> Genome:
new_genes = []
for i in range(const.GENOME_LENGTH):
selection = rd.choices([0, 1], weights=[5, 5], k=1)
if selection[0] == 0:
new_genes.append(genome_1.genes[i])
else:
new_genes.append(genome_2.genes[i])
return Genome(new_genes)
def one_point_crossover(genome_1: Genome, genome_2: Genome) -> Genome:
first_point = randint(0, const.GENOME_LENGTH)
new_genes = []
for i in range(const.GENOME_LENGTH):
if first_point < i:
new_genes.append(genome_1.genes[i])
else:
new_genes.append(genome_2.genes[i])
return Genome(new_genes)
def two_point_crossover(genome_1: Genome, genome_2: Genome) -> Genome:
first_point = randint(0, const.GENOME_LENGTH)
# Normally both have to be a random number but it makes sense to start them that way since after the 1st point then the second starts
second_point = randint(first_point, const.GENOME_LENGTH)
new_genes = []
selection = rd.choices([0, 1], weights=[5, 5], k=1)
if selection[0] == 0:
for i in range(const.GENOME_LENGTH):
if i < first_point or i > second_point:
new_genes.append(genome_1.genes[i])
else:
new_genes.append(genome_2.genes[i])
else:
for i in range(const.GENOME_LENGTH):
if i < first_point or i > second_point:
new_genes.append(genome_2.genes[i])
else:
new_genes.append(genome_1.genes[i])
return Genome(new_genes)
def __init__(self, individuals: List = None):
if individuals is None:
self.individuals: List[Genome] = [Genome() for _ in range(Const.N_INDIVIDUALS)]
else:
self.individuals: List[Genome] = individuals
def generate_new(self, next_population):
while len(next_population) < N_INDIVIDUALS:
next_population.append(Genome())
def arithmetic_crossover(genome_1: Genome, genome_2: Genome) -> Genome:
new_genes = []
for i in range(const.GENOME_LENGTH):
new_genes.append((genome_1.genes[i] + genome_2.genes[i]) / 2)
return Genome(new_genes)