为遗传算法创建初始解决方案Python

Question

请帮助创建一个具有以下条件的 initial_solution 变量：

结构

population_list = {"LHS":[], "RHS": []}

字典元素数= population_size = 20

对于每个population_list元素"LHS"和"RHS"元素。

对于"LHS"，有两个job_count = 10元素，每个元素的长度都精确列出一个列表：

max_sublot = [3, 5, 7, 6, 4, 2, 7, 9, 3, 5]

它的值是一个随机值[0,1），四舍五入到两位小数。

因为"RHS"总共有max_sublot * mc_op个元素。

max_sublot = [3, 5, 7, 6, 4, 2, 7, 9, 3, 5]
mc_op = [6, 14, 8, 5, 6, 9, 4, 6, 7, 2]

每个元素长度= 4，根据random of range job_count的每个值，1值为max_sublot，根据每个值operation_count = 10的2为随机数，根据mc_op的范围为3的随机数，根据每个的长度为4 import numpy as np population_size = 20 job_count = 10 operation_count = 10 max_sublot = [3, 5, 7, 6, 4, 2, 7, 9, 3, 5] mc_op = [6, 14, 8, 5, 6, 9, 4, 6, 7, 2] class Population_list(object): def __init__(self, LHS, RHS): self.LHS = LHS self.RHS = RHS population_list = {"LHS":[], "RHS": []} for i in range (population_size): for j in range(job_count): for s in max_sublot: lhs_random_num = list(np.random.random()) population_list.update("LHS") print(population_list)

的值

这是GA初始解决方案的演示，如下图：

作为我的意见，请您为它确定合适的数据结构，如下所示：

git rm --cached `git ls-files -i --exclude-from=.gitignore`

Answer 1

我认为您需要这样的东西

population_size = 20
job_count = 10
operation_count = 10
max_sublot = [3, 5, 7, 6, 4, 2, 7, 9, 3, 5]
mc_op = [6, 14, 8, 5, 6, 9, 4, 6, 7, 2]
import numpy as np

def gen_population(population_size, max_sublot, mc_op, job_count):
    return tuple({'LHS': [gen_lhs(length) for length in max_sublot],
                  'RHS': gen_rhs(np.dot(max_sublot, mc_op), job_count, max_sublot, 10, mc_op)} for _ in range(population_size))


def gen_lhs(length):
    return [round(np.random.uniform(0,1),2) for _ in range(length)]

def gen_rhs(length, job_count, max_sublot, operation_count, mc_op):
    ret = []
    for i in range(length):
        new = []
        new.append(np.random.randint(job_count))
        new.append(np.random.choice(max_sublot))
        new.append(np.random.randint(operation_count))
        new.append(np.random.choice(mc_op))
        ret.append(new)
    return ret

gen_population(population_size, max_sublot, mc_op, job_count)