def CrossOver_Of_Generation(self, parent1, parent2):
slice_index = random.randint(1, self.Size_Of_Problem - 1)
child1_chrom = self.CrossOver_Of_Chromosomes(slice_index,
parent1.chromosomes,
parent2.chromosomes)
child2_chrom = self.CrossOver_Of_Chromosomes(slice_index,
parent2.chromosomes,
parent1.chromosomes)
assert (len(child1_chrom) == len(child2_chrom) == self.Size_Of_Problem)
child1 = Individual(self.Size_Of_Problem)
child1.chromosomes = child1_chrom
child2 = Individual(self.Size_Of_Problem)
child2.chromosomes = child2_chrom
return child1, child2
def genetic_crossover(self, parent1, parent2):
"""
Mixes the two parent individuals into two children slicing them by a
random index and avoiding repeating chromosomes in eahc child
"""
slice_index = random.randint(1, self.problem_size - 1)
child1_chrom = self.croosover_chromosomes(slice_index,
parent1.chromosomes,
parent2.chromosomes)
child2_chrom = self.croosover_chromosomes(slice_index,
parent2.chromosomes,
parent1.chromosomes)
assert (len(child1_chrom) == len(child2_chrom) == self.problem_size)
child1 = Individual(self.problem_size)
child1.chromosomes = child1_chrom
child2 = Individual(self.problem_size)
child2.chromosomes = child2_chrom
return child1, child2
