def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
algorithm = HillClimbing(max_gen)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
pop_size = int(self.pop_size.text())
num_children = int(self.num_children.text())
algorithm = EvolutionStrat(max_gen, pop_size, num_children)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
pop_size = int(self.pop_size.text())
clone_f = float(self.clone_f.text())
num_rand = int(self.num_rand.text())
algorithm = ClonalSelection(max_gen, pop_size, clone_f, num_rand)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
pop_size = int(self.pop_size.text())
weight_f = float(self.weight_f.text())
cross_r = float(self.cross_r.text())
algorithm = DiffEvolution(max_gen, pop_size, weight_f, cross_r)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:'+str(error))
def run_algorithm(self):
try:
pop_size = int(self.pop_size.text())
best_p = int(self.best_pop.text())
max_gen = int(self.max_gen.text())
p_m = float(self.p_m.text())
algorithm = Genetic(pop_size, best_p, max_gen, p_m)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:'+str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
mem_size = int(self.mem_size.text())
consid_r = float(self.consid_r.text())
adjust_r = float(self.adjust_r.text())
rang = float(self.rang.text())
algorithm = Harmony(max_gen, mem_size, consid_r, adjust_r, rang)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
num_samples = int(self.num_samples.text())
num_update = int(self.num_update.text())
learning_r = float(self.learning_r.text())
algorithm = CrossEntropy(max_gen, num_samples, num_update,
learning_r)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
pop_size = int(self.pop_size.text())
num_clones = int(self.num_clones.text())
beta = int(self.beta.text())
num_rand = int(self.num_rand.text())
algorithm = ImmuneNetwork(max_gen, pop_size, num_clones, beta,
num_rand)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
pop_size = int(self.pop_size.text())
p_cross = float(self.p_cross.text())
max_local_gens = int(self.max_local_gens.text())
p_mut = float(self.p_mut.text())
p_local = float(self.p_local.text())
algorithm = Memetic(max_gen, pop_size, p_cross, p_mut,
max_local_gens, p_local)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
def run_algorithm(self):
try:
max_gen = int(self.max_gen.text())
init_f = float(self.init_f.text())
s_factor = float(self.s_factor.text())
l_factor = float(self.l_factor.text())
iter_mult = int(self.iter_mult.text())
max_no_impr = int(self.max_no_impr.text())
algorithm = AdaptativeRandomS(max_gen, init_f, s_factor, l_factor,
iter_mult, max_no_impr)
val, t_time = Runner.run_algorithm(algorithm, self.title)
self.print_results(val, t_time)
except ValueError as error:
QMessageBox.warning(self, 'Value error',
'Invalid input:' + str(error))
