def execute_algorithm(generations,population_size,vector_functions,vector_variables,available_expressions,decimal_precision,
community_class,algorithm_class,algorithm_options,representation_class,representation_options,
fitness_class,fitness_options,shared_fitness_class,shared_fitness_options,selection_class,selection_options,
crossover_class,crossover_options,mutation_class,mutation_options,elitism_amount):
result_instances = vr.verify_algorithm_settings(generations,population_size,decimal_precision,community_class,algorithm_class,representation_class,
fitness_class,shared_fitness_class,selection_class,crossover_class,mutation_class,elitism_amount)
results = []
if "ERROR" in result_instances:
for element in algorithm_instances:
if "ERROR" not in element:
result_instances.remove(perro)
results = result_instances
else:
community_instance = result_instances[0]
algorithm_instance = result_instances[1]
representation_instance = result_instances[2]
fitness_instance = result_instances[3]
shared_fitness_instance = result_instances[4]
selection_instance = result_instances[5]
crossover_instance = result_instances[6]
mutation_instance = result_instances[7]
results = getattr(algorithm_instance,"execute_moea")(generations,population_size,vector_functions,vector_variables,available_expressions,
decimal_precision,community_instance,algorithm_options,representation_instance,representation_options,
fitness_instance,fitness_options,shared_fitness_instance,shared_fitness_options,
selection_instance,selection_options,crossover_instance,crossover_options,
mutation_instance,mutation_options,elitism_amount)
return results
