def run_one_max_problem():
generator = create_chromosome_generator()
ev_alg = create_evolutionary_algorithm()
island = Island(ev_alg, generator, population_size=10)
display_best_individual(island)
island.evolve(num_generations=50)
display_best_individual(island)
def main():
crossover = SinglePointCrossover()
mutation = SinglePointMutation(get_random_float)
selection = Tournament(10)
fitness = ZeroMinFitnessFunction()
local_opt_fitness = ContinuousLocalOptimization(fitness)
evaluator = Evaluation(local_opt_fitness)
ea = MuPlusLambda(evaluator, selection, crossover, mutation, 0.4, 0.4, 20)
generator = MultipleFloatChromosomeGenerator(get_random_float, 8)
island = Island(ea, generator, 25)
island.evolve(1)
report_max_min_mean_fitness(island)
island.evolve(500)
report_max_min_mean_fitness(island)
def test_island_hof(mocker):
hof = mocker.Mock()
crossover = SinglePointCrossover()
mutation = SinglePointMutation(mutation_function)
selection = Tournament(10)
fitness = MultipleValueFitnessFunction()
evaluator = Evaluation(fitness)
ev_alg = MuPlusLambda(evaluator, selection, crossover, mutation,
0.2, 0.4, 20)
generator = MultipleValueChromosomeGenerator(mutation_function, 10)
island = Island(ev_alg, generator, 25, hall_of_fame=hof)
island.evolve(10)
hof.update.assert_called_once()
hof_update_pop = hof.update.call_args[0][0]
for h, i in zip(hof_update_pop, island.population):
assert h == i