def __init__(self, number_tables, table_size, guest_list):
# arrangement_list is population
self.arrangement_list = []
self.table_size = table_size
self.number_tables = number_tables
self.guest_list = copy.deepcopy(guest_list)
for i in range(POPULATION_SIZE):
new_gl = copy.deepcopy(self.guest_list)
self.arrangement_list.append(
Arrangement(self.number_tables, self.table_size, new_gl))
for arr_ in self.arrangement_list:
arr_.create_tables()
arr_.seat_guests()
def evolve_one_generation_b(self):
# for each window select parents
range_of_arrangements = int(POPULATION_SIZE / WINDOW_SIZE)
rand.shuffle(self.arrangement_list)
diversity_for_avg = []
new_arrangements = []
for i in range(range_of_arrangements):
window = copy.deepcopy(self.arrangement_list[:WINDOW_SIZE])
del (self.arrangement_list[:WINDOW_SIZE])
for arrangement in window:
arrangement.get_fitness()
window.sort(key=lambda arr: arr.fitness) # get best 2 parents
parent1, parent2 = window[0], window[1] # PARENT SELECTION HERE
# cross_over
p1_master_list = copy.deepcopy(parent1.export_master_list())
p2_master_list = copy.deepcopy(parent2.export_master_list())
p1_for_child1 = copy.deepcopy(p1_master_list)
p2_for_child1 = copy.deepcopy(p2_master_list)
p1_for_child2 = copy.deepcopy(p1_master_list)
p2_for_child2 = copy.deepcopy(p2_master_list)
child_list1 = self.pmx_crossover(p1_for_child1, p2_for_child1,
self.table_size)
child_list2 = self.pmx_crossover(p1_for_child2, p2_for_child2,
self.table_size)
list_for_mutating = [] # list of lists
for i_ in range(MUTANT_GROUPS):
ch1_mutant = copy.deepcopy(child_list1)
ch2_mutant = copy.deepcopy(child_list2)
list_for_mutating.append(ch1_mutant)
list_for_mutating.append(ch2_mutant)
for new_mutant in list_for_mutating:
self.mutate(new_mutant, LIMIT_MUTATIONS)
list_of_new_mutants = [] # list of Arrangement objects
for new_mutant in list_for_mutating:
guest_list_copy = copy.deepcopy(self.guest_list)
arrangement = Arrangement(self.number_tables, self.table_size,
guest_list_copy)
# break continutous list of guests back into their seperate tables
now_seperate = [
new_mutant[x:x + self.table_size]
for x in range(0, len(new_mutant), self.table_size)
]
table_list = []
for index, list_ in enumerate(now_seperate):
table = Table(self.table_size, index)
table.guests = list_
table_list.append(table)
arrangement.tables = table_list
list_of_new_mutants.append(arrangement)
# now list_of_new_mutants [] has mutated arrangement objects ready for survivor selection
for arrangement in list_of_new_mutants:
arrangement.get_fitness()
parent1_group = []
parent2_group = []
for arr in list_of_new_mutants:
div_1 = self.measure_diversity(arr, parent1)
div_2 = self.measure_diversity(arr, parent2)
if div_1 < div_2:
parent1_group.append(arr)
else:
parent2_group.append(arr)
parent1_group.sort(key=lambda arr: arr.fitness)
parent2_group.sort(key=lambda arr: arr.fitness)
# Attempting to add some diversity here, we want SOME suboptimal solutions to pass
# so that they may end up evolving into even better solutions
if parent1_group:
self.add_randomness(parent1_group,
LIMIT_CHANGES_SURVIVOR_SELECTION)
if parent2_group:
self.add_randomness(parent2_group,
LIMIT_CHANGES_SURVIVOR_SELECTION)
# for i in range(WINDOW_SIZE - 2):
if WITH_REPLACEMENT:
survivors = [parent1, parent2]
else:
survivors = []
p1_index = 0
p2_index = 0
while len(survivors) < WINDOW_SIZE:
if i % 2 == 0:
if parent1_group:
survivors.append(parent1_group[p1_index])
p1_index += 1
else:
survivors.append(parent2_group[p2_index])
p2_index += 1
else:
if parent2_group:
survivors.append(parent2_group[p2_index])
p2_index += 1
else:
survivors.append(parent1_group[p1_index])
p1_index += 1
i += 1
for survivor in survivors:
new_arrangements.append(survivor)
diversity = self.measure_diversity(parent1, parent2)
diversity_for_avg.append(diversity)
print("Parents fitness(1, 2): {} {} Their Diversity: {}".format(
parent1.fitness, parent2.fitness, diversity))
avg_diversity = sum(diversity_for_avg) / len(diversity_for_avg)
print("Average diversity between parents: ", avg_diversity)
self.arrangement_list = new_arrangements
top_three_diversity = self.top_three_diversity()
print("Diversity for the top three in the next generation: ",
top_three_diversity)
def __init__(self):
Arrangement.__init__(self, "baby's breath", 4)
MothersDay.__init__(self, "white", 0, 0)
def __init__(self):
Arrangement.__init__(self, "poppies", 4)
MothersDay.__init__(self, "red", 0, 0)
def __init__(self):
Arrangement.__init__(self, "daisies", 4)
MothersDay.__init__(self, "white", 0, 0)
def __init__(self):
Arrangement.__init__(self, "rose", 7)
ValentinesDay.__init__(self, "red", 0, 0)