def start_pso():
logger.info("*" * 80)
logger.info("*" * 80)
logger.info("Particle Swarm Optimization")
logger.info("*" * 80)
logger.info("Number of Generations: %s", NUMBER_OF_GENERATIONS)
logger.info("Population Size: %s", POPULATION_SIZE)
logger.info("Function: %s", SELECTED_FUNCTION)
logger.info("Epsilon: %s", EPSILON)
logger.info("*" * 80)
logger.info("*" * 80)
# Generate population[] of Particle()
population = generate_population()
# Get the best position in population
best_of_all = get_best_of_all(population, population[0].best)
logger.info("Best: %s Fitness: %s", best_of_all, evaluate(best_of_all))
for y in range(NUMBER_OF_GENERATIONS):
if abs(evaluate(best_of_all)) < EPSILON: # Stop condition
logger.info("*" * 80)
logger.info("Best solution found at %s generation.", y)
logger.info("Best of all: %s Fitness: %s", str(best_of_all), str(evaluate(best_of_all)))
logger.info("*" * 80)
break
for particle in population:
# Move each particle using its velocity
particle.move_position(best_of_all)
# Update best position ever in population's history
best_of_all = get_best_of_all(population, best_of_all)
# logger,info("%s", particle)
if y % PRINTING_INTERVAL == 0:
logger.debug("-" * 80)
logger.debug("Generation: %s", y)
logger.debug("Best of all: %s Fitness: %s", str(best_of_all), str(evaluate(best_of_all)))
logger.debug("-" * 80)
logger.info("*" * 80)
logger.info("No better solution found. ")
logger.info("Best solution at %s generation", NUMBER_OF_GENERATIONS)
logger.info("Best of all: %s Fitness: %s", str(best_of_all), str(evaluate(best_of_all)))
logger.info("*" * 80)
return population
def start_pso():
logger.info("*" * 80)
logger.info("*" * 80)
logger.info("Particle Swarm Optimization")
logger.info("*" * 80)
logger.info("Number of Generations: %s", NUMBER_OF_GENERATIONS)
logger.info("Population Size: %s", POPULATION_SIZE)
logger.info("Function: %s", SELECTED_FUNCTION)
logger.info("Epsilon: %s", EPSILON)
logger.info("*" * 80)
logger.info("*" * 80)
# Generate population[] of Particle()
population = generate_population()
# Get the best position in population
best_of_all = get_best_of_all(population, population[0].best)
logger.info("Best: %s Fitness: %s", best_of_all, evaluate(best_of_all))
for y in range(NUMBER_OF_GENERATIONS):
if abs(evaluate(best_of_all)) < EPSILON: # Stop condition
logger.info("*" * 80)
logger.info("Best solution found at %s generation.", y)
logger.info("Best of all: %s Fitness: %s", str(best_of_all),
str(evaluate(best_of_all)))
logger.info("*" * 80)
break
for particle in population:
# Move each particle using its velocity
particle.move_position(best_of_all)
# Update best position ever in population's history
best_of_all = get_best_of_all(population, best_of_all)
# logger,info("%s", particle)
if y % PRINTING_INTERVAL == 0:
logger.debug("-" * 80)
logger.debug("Generation: %s", y)
logger.debug("Best of all: %s Fitness: %s", str(best_of_all),
str(evaluate(best_of_all)))
logger.debug("-" * 80)
logger.info("*" * 80)
logger.info("No better solution found. ")
logger.info("Best solution at %s generation", NUMBER_OF_GENERATIONS)
logger.info("Best of all: %s Fitness: %s", str(best_of_all),
str(evaluate(best_of_all)))
logger.info("*" * 80)
return population
def show_population(population, fitness):
logger.info("Population ")
for index in range(0, POPULATION_SIZE):
logger.info("%f => %f", (population[index], fitness[index]))
def start_evaluation():
logger.info("*" * 80)
logger.info("*" * 80)
logger.info("Starting Strassen Finder")
logger.info("*" * 80)
logger.info("Number of Generations: %s", NUMBER_OF_GENERATIONS)
logger.info("Chromosome Length: %s", CHROMOSOME_LENGTH)
logger.info("Population Size: %s", POPULATION_SIZE)
logger.info("*" * 80)
logger.info("*" * 80)
# generating population
population = generate_population(-1, 1)
fitness = strassen_fitness(population)
#
ancestor = fitness[0]
for i in range(0, NUMBER_OF_GENERATIONS):
if fitness[0] < EPSILON:
logger.info("*" * 80)
logger.info("Best solution found at %s generation.", i)
logger.info(population[0])
logger.info(fitness[0])
logger.info("*" * 80)
break
# There's no change, let's create an unfortunate event!
if (ancestor == fitness[0]) and (i % (PRINTING_INTERVAL / 2) == 0):
logger.debug("Wake Up!!!!")
new_sons = one_point_crosses(population[0], population[1])
population[2] = new_sons[0]
population[-1] = random_mutation(population[-1], -1, 1)
else:
ancestor = fitness[0]
new_population = generate_new_population(population,
fitness,
mutator=strassen_mutation)
population = sorted(new_population,
key=evaluate_product,
reverse=False)[0:POPULATION_SIZE]
fitness = strassen_fitness(population)
if i % PRINTING_INTERVAL == 0:
#
logger.debug("-" * 80)
logger.debug("Generation %s ", i)
logger.debug("BEST :")
logger.debug("Single %s ", population[0])
logger.debug("Fitness %s ", fitness[0])
logger.debug("." * 80)
logger.debug("WORST :")
logger.debug("Single %s ", population[-1])
logger.debug("Fitness %s ", fitness[-1])
logger.debug("-" * 80)
logger.info("*" * 80)
logger.info("No better solution found. ")
logger.info("Best solution at %s generation", NUMBER_OF_GENERATIONS)
logger.info(population[0])
logger.info(fitness[0])
logger.info("*" * 80)
return population
def show_population(population, fitness):
logger.info("Population ")
for index in range(0, POPULATION_SIZE):
logger.info("%f => %f", (population[index], fitness[index]))