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Updated commenting and removed old survivor selection method

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Updated commenting and removed old survivor selection method
This commit is contained in:
RyleyGG
2020-10-12 16:11:41 -04:00
parent 94d7c52666
commit 96a1177a67
1 changed files with 6 additions and 27 deletions
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33
src/survivor_selection/survivor_selection_methods.py
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@ -7,36 +7,15 @@ from initialization.chromosome_structure.chromosome import Chromosome
class Survivor_Selection: class Survivor_Selection:
"""Survivor selection determines which individuals should be brought to the next generation""" """Survivor selection determines which individuals should be brought to the next generation"""
""" Pretty sure this isn't actually survivor selection - seems like its 'cheating'
def repeated_crossover(ga, next_population):
while len(next_population.get_all_chromosomes()) < ga.population_size:
crossover_pool = ga.population.mating_pool
split_point = random.randint(0,ga.chromosome_length)
chromosome_list = []
for i in range(len(crossover_pool)):
if i + 1 < len(crossover_pool):
new_gene_set = []
parent_one = crossover_pool[i].get_genes()
parent_two = crossover_pool[i+1].get_genes()
new_gene_set.extend(parent_one[0:split_point])
new_gene_set.extend(parent_two[split_point:])
new_chromosome = create_chromosome(new_gene_set)
chromosome_list.append(new_chromosome)
for i in range(len(chromosome_list)):
next_population.add_chromosome(chromosome_list[i])
if len(next_population.get_all_chromosomes()) >= ga.population_size:
break
return next_population
"""
"""Will bring all but the worst-performing chromosomes from the current generation"""
"""The exact number of chromosomes removed depends on how many offspring were generated by parent selection"""
def remove_worst(ga, next_population): def remove_worst(ga, next_population):
"""
Will bring all but the worst-performing chromosomes from the current generation.
The exact number of chromosomes removed depends on how many offspring were generated by parent selection.
"""
iterator = 0 iterator = 0
# While the size of the next population is less than it should be (as determined by the user)
while len(next_population.get_all_chromosomes()) < ga.population_size: while len(next_population.get_all_chromosomes()) < ga.population_size:
# Add the best chromosome from the current population that hasn't already been brought over
next_population.add_chromosome(ga.population.get_all_chromosomes()[iterator]) next_population.add_chromosome(ga.population.get_all_chromosomes()[iterator])
iterator += 1 iterator += 1
return next_population return next_population