def objective_functions(chro_str):
pheno_type = BinaryChromosome.get_phenotype(chro_str)
buildable, factory = utils.create_factory_from_pheno_type(pheno_type, production_line, False)
factory.simulate(simulation_time)
labor = factory.num_labor
num_unit = factory.num_unit
return np.array([-labor, num_unit])
def save_generation_info_to_excel(generation_dict,
production_line,
file_path,
intialize=False):
num_objective = MultiObjectiveAnalyzer.get_num_objective(
generation_dict[1])
row_list = []
for num, generation, time in generation_dict.values():
for chromosome_info in generation:
chro_list = []
chro_list.extend([num, time, chromosome_info[0]])
for idx in range(0, num_objective):
chro_list.append(chromosome_info[1][idx])
pheno_info = BinaryChromosome.get_phenotype(chromosome_info[0])
cycle_time = utils.cycle_time_from_pheno_type(pheno_info)
chro_list.append(cycle_time)
row_list.append(chro_list)
save_info_row = deepcopy(MultiObjectiveAnalyzer.basic_save_info_row)
for idx in range(0, num_objective):
save_info_row.append('objectvie' + str(idx + 1))
save_info_row.append('cycle_time')
df = DataFrame(row_list, columns=save_info_row)
with ExcelWriter(file_path, engine='xlsxwriter') as writer:
df.to_excel(excel_writer=writer,
sheet_name='result',
header=True,
index=False)
return
def create_factory_from_chromosome(chromosome,
production_line,
initialize=False):
pheno_type = BinaryChromosome.get_phenotype(chromosome)
buildable, factory = utils.create_factory_from_pheno_type(
pheno_type, production_line, initialize=initialize)
return buildable, factory
def factory_build_check_2(chromosome, new_generation):
check = True
pheno_type = BinaryChromosome.get_phenotype(chromosome)
cycle_time_idx = pheno_type['cycle_time']
if cycle_time_idx >= len(production_line.cycle_dict):
return False
buildable, factory = utils.create_factory_from_pheno_type(pheno_type, production_line, False)
if not buildable:
return buildable
for chromosome_info in new_generation:
chro_2 = chromosome_info[0]
pheno_type_2 = BinaryChromosome.get_phenotype(chro_2)
buildable, factory_2 = utils.create_factory_from_pheno_type(pheno_type_2, production_line, False)
if factory == factory_2:
check = False
break
return check
def factory_build_check(chromosome):
pheno_type = BinaryChromosome.get_phenotype(chromosome)
buildable, factory = utils.create_factory_from_pheno_type(
pheno_type, production_line, False)
return buildable
from moga.chromosome import BinaryChromosome
from module_factory.optimization.analysis import MultiObjectiveAnalyzer
from module_factory.component.production_line import ProductionLine
from module_factory.optimization import utils
from pandas import ExcelWriter, DataFrame
import pickle
# set BinaryChromosome from production line file
production_line = ProductionLine('sample_data/production_line_200903.csv')
geno_shape = utils.production_line_to_geno_shape(production_line)
BinaryChromosome.set_geno_shape(**geno_shape)
# set fitness check function
def factory_build_check(chromosome):
pheno_type = BinaryChromosome.get_phenotype(chromosome)
buildable, factory = utils.create_factory_from_pheno_type(
pheno_type, production_line, False)
return buildable
BinaryChromosome.fitted_in_geno_func_list.append(factory_build_check)
with open('experiment/test.ge', 'rb') as f:
generation_dict = pickle.load(f)
## evolution process to fig
# MultiObjectiveAnalyzer.save_generation_info_to_excel(generation_dict, 'test_1.xlsx')
# MultiObjectiveAnalyzer.save_evolution_process_to_fig(generation_dict, 'test.png')
## compare process to fig