def set_best_makespan(self):
## List sorted to get the best end
makespan_sorted = sorted(self.makespan, key=self.get_end, reverse=True)
current_best: Activity = Activity.empty_activity()
current_best.end = 1000000
index_current_best = 0
if not len(self.best_makespan) == 0:
current_best: Activity = self.best_makespan[len(self.best_makespan)
- 1]
new_best: Activity = makespan_sorted[0]
is_better = new_best.end < current_best.end
if is_better:
index: int = self.makespan.index(new_best)
self.best_makespan = copy.deepcopy(self.chromosomes[index].genes)
self.fitness_reference = copy.deepcopy(new_best)
for chromosome in self.chromosomes:
act = max(chromosome.genes, key=self.get_end)
new_fitness = float(new_best.end) / float(act.end)
chromosome.fitness = new_fitness
#print(f'new fitness {new_fitness}')
print('\n\nCurrent best: ')
current_best.print_activity()
print('New best: ')
self.best_makespan[len(self.best_makespan) - 1].print_activity()
print('\n')
def __init__(self, nPob: int, generations, mutation_rate: float = 0.3):
if (not nPob % 2 == 0 or not nPob > 2):
raise Exception(
f'The populations must be an even number {nPob} and greater than 2'
)
self.nPob = nPob
self.chromosomes = []
self.makespan = []
self.best_makespan = []
self.generations = generations
self.mutation_rate = mutation_rate
self.fitness_reference = Activity.empty_activity()
