def _eval_deadlines(indiv):
_debug('_eval_deadlines')
for t in indiv.tasks:
if t.begin + t.duration > t.deadline:
indiv.fitness -= abs(((t.begin + t.duration) - t.deadline) * 4)
elif t.begin + t.duration == t.deadline:
indiv.fitness += 8
else:
indiv.fitness -= abs((t.begin + t.duration) - t.deadline)
def _mutate_individual(indiv):
_debug('_mutate_individual')
newindiv = indiv.__copy__()
for t in newindiv.tasks:
if uniform(0, 1) >= 0.5:
if uniform(0, 1) >= 0.5:
t.begin += max(0, int(uniform(1, t.duration / 4)))
else:
t.begin -= max(0, int(uniform(1, t.duration / 4)))
return newindiv
def _mutate_population(population):
_debug('_mutate_population')
size = len(population)
for i in range(size / 2):
j = int(uniform(0, size))
newindiv = _mutate_individual(population[j])
while newindiv in population:
_debug('_mutate_population: newindiv in population')
newindiv = _mutate_individual(population[j])
_eval_individual(newindiv)
population += [newindiv]
population.sort(lambda a, b: cmp(b.fitness, a.fitness))
return population[:size]
def _initial_population(schedule):
_debug('_initial_population')
population = [schedule]
population_size = 50
while len(population) < population_size:
newindiv = _mutate_individual(population[int(
uniform(0, len(population)))])
while newindiv in population:
_debug('_initial_population: newindiv in population')
newindiv = _mutate_individual(population[int(
uniform(0, len(population)))])
_eval_individual(newindiv)
population += [newindiv]
population.sort(lambda a, b: cmp(b.fitness, a.fitness))
return population
def _eval_overlaps(indiv):
_debug('_eval_overlaps')
num_overlaps = 0
penalty = 0
for t in indiv.tasks:
for t2 in indiv.tasks:
if t.begin + t.duration >= t2.begin and \
t.begin + t.duration <= t2.begin + t2.duration:
penalty += ((t.begin + t.duration - t2.begin) + 1)
num_overlaps += 1
for t2 in indiv.fixedtasks:
if t.begin + t.duration >= t2.begin and \
t.begin + t.duration <= t2.begin + t2.duration:
penalty += ((t.begin + t.duration - t2.begin) + 1)
num_overlaps += 1
indiv.fitness -= (penalty * num_overlaps)
def start(schedule):
elite_iterations = 0
elite_individual = schedule
iterations = 100
_initial_individual(schedule)
population = _initial_population(schedule)
for i in range(iterations):
_debug('iteration ' + str(i))
population = _mutate_population(population)
if population[0] == elite_individual:
elite_iterations += 1
else:
elite_individual = population[0]
elite_iterations = 0
if elite_iterations == iterations / 2:
break
return population[0]
def _eval_individual(indiv):
_debug('_eval_individual')
indiv.fitness = 0
_eval_deadlines(indiv)
_eval_overlaps(indiv)
def _initial_individual(schedule):
_debug('_initial_individual')
for t in schedule.tasks:
t.begin = t.deadline - t.duration
_eval_individual(schedule)