genetic_algorithm.py 文件源码

def begin(self):
        for i in range(1000):
            index1 = self.choose_gene(random.random())
            index2 = self.choose_gene(random.random())
            while index1 == index2:
                index2 = self.choose_gene(random.random())

            if random.random() < self.mutation_prob:
                self.genes[index1].mutation()
                self.genes[index2].mutation()

            if random.random() < self.cross_prob:
                Gene.cross(self.genes[index1], self.genes[index2])

            self.get_fit_value()
            # self.gene_pop()

            result = self.get_best_gene()
            print len(self.genes), result[0].bin2dec(), result[1]