遗传算法线性交叉

import numpy as np
import geatpy as ea
import random

pop_1=np.array([[1, 11, 21,9,16,10,8,17],
                  [2, 12, 22,10,17,11,9,18],
                  [3, 13, 23,11,18,12,10,19],
                  [4, 14, 24,12,19,13,11,20],
                  [5, 15, 25,13,20,14,12,21],
                  [6, 16, 26,14,21,15,13,22],
                  [7, 17, 27,15,22,16,14,23],
                  [8, 18, 28,16,23,17,15,24]])
def crossover(pop_1,pc):
    j=0
    while j<=3:
        row_rand_array = np.arange(pop_1.shape[0])
        np.random.shuffle(row_rand_array)  # 现场修改序列，改变自身内容。（类似洗牌，打乱顺序）
        chorm = pop_1[row_rand_array[0:2]]  # 抽取pop_1中的两个个体染色体。数组
        c_point1 = random.randint(0, len(chorm[0])-1)
        c_point2 = random.randint(0, len(chorm[0])-1)
        if c_point1 <= c_point2:
            s_point = c_point1
            e_point = c_point2
        else:
            s_point = c_point2
            e_point = c_point1
        print(s_point, e_point)
        # r = random.random()
        if 0.8 <= 0.7:
            new_C = chorm
            print(new_C)
        else:
            a = random.random()
            b = random.random()
            print(a, b)
            chrom_n1 = chorm[0]  # 父代1
            chrom_n2 = chorm[1]  # 父代2
            print(chrom_n1,chrom_n2)
            for i in range(s_point, e_point + 1):  # 遍历每个交叉点
                Ge1 = int(chrom_n1[i])
                Ge2 = int(chrom_n2[i])
                print(Ge1, Ge2)
                Ge1 = Ge2 + a * (Ge1 - Ge2)
                Ge2 = Ge1 + b * (Ge2 - Ge1)  # 交叉后的基因
                print(Ge1, Ge2)
                chrom_n1[i] = Ge1
                chrom_n2[i] = Ge2  # 更新染色体
                # print(chorm_n1, chorm_n2)
            # print(chorm_n1, chorm_n2)  # 注意缩进，只要最后每个点交叉后最终的迭代结果
            pop_1[row_rand_array[0:1]] = chrom_n1
            pop_1[row_rand_array[1:2]] = chrom_n2  # 更新整个种群，将交叉后的染色体存入种群中
            # pop_c = pop_1  # print(pop_c) #已经是更新后的种群了
        j +=1
        print(j)
    return pop_1

dxs=crossover(pop_1,0.7)
print(dxs)