simulated_annealing.py 文件源码

def begin(self):
        x = random.randint(self.x_range[0], self.x_range[1])
        f = self.func(x)
        T = self.T0
        while T > self.T_min:
            for i in range(self.K):
                new_x = self.gen_new_x(x, T)
                f_x = self.func(new_x)
                delta_E = f_x - f
                #
                if delta_E < 0:
                    f = f_x
                    x = new_x
                    break
                else:
                    #p_k = 1.0 / (1 + np.exp(- delta_E / self.func(T)))
                    p_k = np.exp(- delta_E / T)
                    if random.random() < p_k:
                        f = f_x
                        x = new_x
                        break
            T *= self.delta

        return x