def Evolution(self, MRate, CRate, nGenerations):
self.MRate = MRate
self.CRate = CRate
self.nGenerations = nGenerations
# creates the initial population
pop = Population(self.size_pop)
pop.create_new(self.Matrix_inf, self.size_pop, self.nGenes, True, self.IniCoordinate, self.FinalCoordinate)
fittest = pop.Fittest(self.size_pop)
print("Path: ", fittest.genes, "Cost:", fittest.cost, "Fitness:", fittest.fitness)
self.resultado_fitness.append(fittest.fitness)
self.resultado_generation.append(0)
##evolves the initial population in n generations
for i in range(1,self.nGenerations):
pop = self.create_new_generation(pop)
fittest = pop.Fittest(self.size_pop)
print("Path: ", fittest.genes, "Cost:", fittest.cost,"Fitness:", fittest.fitness)
self.resultado_fitness.append(fittest.fitness)
self.resultado_generation.append(i)
fittest = pop.Fittest(self.size_pop)
##print solution
print("\nSolution:")
print("Path: ", fittest.genes, "Cost:", fittest.cost,"Fitness:", fittest.fitness)
self.fittest_cost = fittest.cost
def selection(self, pop): #Torneio
fitpop = Population(self.size_pop)
quantity = random.randint(1, self.size_pop)
for i in range(quantity):
add = random.randint(0, self.size_pop - 1)
fitpop.chromosomes.append(pop.chromosomes[add])
fit = fitpop.Fittest(quantity)
return (fit)
