def evolutionary_strategies(args):
minmax = (args.min, args.max)
N = args.N
gens = args.gens
solution = common.initialize(N, minmax)
best_fitness = common.fitness(solution[0])
p = 1.5
for gen in range(1, gens):
if gen % 10 == 0:
print("Generation :#%d" % gen)
mutated = mutation.es_mutation(solution, minmax, p)
#print(solution[0])
#print(mutated[0])
#print(list(map(operator.sub, mutated[0], solution[0])))
fitness = common.fitness(mutated[0])
if fitness <= best_fitness:
best_fitness = fitness
solution = mutated
p = 1.5
common.write_data(gen, fitness, 'es.dat')
#elif fitness == best_fitness:
# p = 1
else:
p = 1.5**(-1 / 4)
if fitness == 0:
break
print("#########################")
print("# Strategy : Evolutionary Strategies")
print("# Generations : " + str(gens))
print("# Best Solution Fitness : %.3f" % best_fitness)
print("# Log File : ./es.dat")
print(
"# Graph : Evolutionary_Strategies_Ackleys_Function.png"
)
print("#########################")
common.plot('Evolutionary Strategies: Ackleys Function', 'es.dat')
def evolutionary_strategies(args):
minmax = (args.min, args.max)
N = args.N
gens = args.gens
solution = common.initialize(N,minmax)
best_fitness = common.fitness(solution[0])
p = 1.5
for gen in range(1, gens):
if gen % 10 == 0:
print("Generation :#%d" % gen)
mutated = mutation.es_mutation(solution, minmax, p)
#print(solution[0])
#print(mutated[0])
#print(list(map(operator.sub, mutated[0], solution[0])))
fitness = common.fitness(mutated[0])
if fitness <= best_fitness:
best_fitness = fitness
solution = mutated
p = 1.5
common.write_data(gen, fitness, 'es.dat')
#elif fitness == best_fitness:
# p = 1
else:
p = 1.5 ** (-1/4)
if fitness == 0:
break
print("#########################")
print("# Strategy : Evolutionary Strategies")
print("# Generations : " + str(gens))
print("# Best Solution Fitness : %.3f" % best_fitness)
print("# Log File : ./es.dat")
print("# Graph : Evolutionary_Strategies_Ackleys_Function.png")
print("#########################")
common.plot('Evolutionary Strategies: Ackleys Function', 'es.dat')
parser.add_argument("--max", help="Maximum value", type=int)
parser.add_argument('-g', "--generations", help="Number of Generations",
dest='gens', type=int)
args = parser.parse_args()
minmax = (args.min, args.max)
N = args.N
gens = args.gens
solution = common.initialize(N,minmax)
best_fitness = common.fitness(solution[0])
p = 1.5
for gen in range(1, gens):
mutated = mutation.es_mutation(solution, minmax, p)
fitness = common.fitness(mutated[0])
if fitness <= best_fitness:
best_fitness = fitness
solution = mutated
p = 1.5
common.write_data(gen, fitness, 'data.dat')
else:
p = 1.5 ** (-1/4)
if fitness == 0:
break
def evolutionary_strategies(args):
minmax = common.get_minmax(args.fitness)
N = args.N
gens = args.gens
population_exchange = args.exchange
exchange_individuals = args.iexchange
islands = args.islands
population_list = []
fittest_list = []
best_fitness_list = []
for i in range(0,islands):
population = common.initialize(N,minmax)
fittest, best_fitness = common.fittest(population[0],
args.fitness)
population_list.append(population)
fittest_list.append(fittest)
best_fitness_list.append(best_fitness)
p_list = [0] * islands
successful_cases_list = [0] * islands
for gen in range(1, gens):
if gen % (gens / 10) == 0:
print("Generation :#%d" % gen)
if gen % population_exchange == 0:
print(" -> Exchange in Generation: %d " % gen)
population_list = common.exchange(population_list,
exchange_individuals)
mutated = [[]] * islands
local_fittest = [0] * islands
fitness = [0] * islands
for i in range(0, islands):
mutated[i] = mutation.es_mutation(population_list[i],
minmax, p_list[i])
local_fittest[i], fitness[i] = common.fittest(mutated[i][0],
args.fitness)
if fitness[i] >= best_fitness_list[i]:
fittest_list[i] = local_fittest[i]
best_fitness_list[i] = fitness[i]
successful_cases_list[i] += 1
population = mutated
common.write_data(gen, fitness[i], 'es%d.dat' % i)
p_list[i] = successful_cases_list[i] / gen
print("#########################")
print("# Strategy : Evolutionary Strategies")
print("# Generations : " + str(gens))
fittest = 0
best_fitness = 0
best_island = 0
for i in range(0, islands):
if best_fitness_list[i] > best_fitness:
fittest = fittest_list[i]
best_fitness = best_fitness_list[i]
best_island = i
print("# Best Solution Value : %.3f" % fittest)
print("# Best Solution Fitness : %g" % best_fitness)
print("# Obtained from Island : %d" % best_island)
print("# Log File : ./es%d.dat" % best_island)
print("# Graph : Evolutionary_Strategies_%s.png" %
args.fitness.upper())
print("#########################")
common.plot('Evolutionary Strategies %s' % args.fitness.upper(),
'es%d.dat' % best_island)
files = []
for island in range(0, islands):
common.plot('Evolutionary Strategies %s_islands' % args.fitness.upper(),
'es%d.dat' % island, False)
