遗传算法的交叉概率默认是多少，可以调吗？

[CarrotC]

No description provided.

[guofei9987]

默认算子是全部交叉的，可以只定义算子去调整

[bencq]

可以贡献代码吗？我感觉这个库还有很多东西需要补全的. 比如交叉概率等.

默认算子是全部交叉的，可以只定义算子去调整

[guofei9987]

可以贡献代码吗？我感觉这个库还有很多东西需要补全的. 比如交叉概率等.

默认算子是全部交叉的，可以只定义算子去调整

可以

[abc-hy]

请问这个调交叉率的代码在哪里呢？能共享一下吗？

[guofei9987]

from sko.GA import GA
from sko.operators import crossover

ga = GA(func=lambda x: x[0] ** 2 + (x[1] - 0.05) ** 2 + (x[2] - 0.5) ** 2
        , n_dim=3, size_pop=100, max_iter=500, lb=[-1, -10, -5], ub=[2, 10, 2],
        precision=[1e-7, 1e-7, 1])

ga.register(operator_name='crossover', operator=crossover.crossover_2point_prob, crossover_prob=0.5)

best_x, best_y = ga.run()
print('best_x:', best_x, '\n', 'best_y:', best_y)

[abc-hy]

谢谢。还有一个问题想问下，这个算法可以导出每一代的最优值吗？如何实现呢？

…

On Mon, Jun 28, 2021 at 7:34 AM 郭飞 ***@***.***> wrote: from sko.GA import GA from sko.operators import crossover ga = GA(func=lambda x: x[0] ** 2 + (x[1] - 0.05) ** 2 + (x[2] - 0.5) ** 2 , n_dim=3, size_pop=100, max_iter=500, lb=[-1, -10, -5], ub=[2, 10, 2], precision=[1e-7, 1e-7, 1]) ga.register(operator_name='crossover', operator=crossover.crossover_2point_prob, crossover_prob=0.5) best_x, best_y = ga.run() print('best_x:', best_x, '\n', 'best_y:', best_y) — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#79 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/APF2ZCSG4VKXT7FJLXZACZDTVBT4JANCNFSM4RKQBE6Q> .

[guofei9987]

谢谢。还有一个问题想问下，这个算法可以导出每一代的最优值吗？如何实现呢？
…
On Mon, Jun 28, 2021 at 7:34 AM 郭飞 @.***> wrote: from sko.GA import GA from sko.operators import crossover ga = GA(func=lambda x: x[0] ** 2 + (x[1] - 0.05) ** 2 + (x[2] - 0.5) ** 2 , n_dim=3, size_pop=100, max_iter=500, lb=[-1, -10, -5], ub=[2, 10, 2], precision=[1e-7, 1e-7, 1]) ga.register(operator_name='crossover', operator=crossover.crossover_2point_prob, crossover_prob=0.5) best_x, best_y = ga.run() print('best_x:', best_x, '\n', 'best_y:', best_y) — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#79 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/APF2ZCSG4VKXT7FJLXZACZDTVBT4JANCNFSM4RKQBE6Q .

https://github.com/guofei9987/scikit-opt/blob/master/examples/demo_ga.py

[abc-hy]

我在代码里输入了这个来设置交叉率，但是报错。请问是什么问题呢？ [image: image.png] [image: image.png]

…

On Fri, Jul 2, 2021 at 8:39 AM 郭飞 ***@***.***> wrote: 谢谢。还有一个问题想问下，这个算法可以导出每一代的最优值吗？如何实现呢？ … <#m_-4931148214033621750_> On Mon, Jun 28, 2021 at 7:34 AM 郭飞 *@*.***> wrote: from sko.GA import GA from sko.operators import crossover ga = GA(func=lambda x: x[0] ** 2 + (x[1] - 0.05) ** 2 + (x[2] - 0.5) ** 2 , n_dim=3, size_pop=100, max_iter=500, lb=[-1, -10, -5], ub=[2, 10, 2], precision=[1e-7, 1e-7, 1]) ga.register(operator_name='crossover', operator=crossover.crossover_2point_prob, crossover_prob=0.5) best_x, best_y = ga.run() print('best_x:', best_x, '\n', 'best_y:', best_y) — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#79 (comment) <#79 (comment)>>, or unsubscribe https://github.com/notifications/unsubscribe-auth/APF2ZCSG4VKXT7FJLXZACZDTVBT4JANCNFSM4RKQBE6Q . https://github.com/guofei9987/scikit-opt/blob/master/examples/demo_ga.py — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#79 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/APF2ZCWOVITL54TGS66AE4LTVW6SFANCNFSM4RKQBE6Q> .

[guofei9987]

我在代码里输入了这个来设置交叉率，但是报错。请问是什么问题呢？ [image: image.png] [image: image.png]
…
On Fri, Jul 2, 2021 at 8:39 AM 郭飞 @.> wrote: 谢谢。还有一个问题想问下，这个算法可以导出每一代的最优值吗？如何实现呢？ … <#m_-4931148214033621750_> On Mon, Jun 28, 2021 at 7:34 AM 郭飞 @.> wrote: from sko.GA import GA from sko.operators import crossover ga = GA(func=lambda x: x[0] ** 2 + (x[1] - 0.05) ** 2 + (x[2] - 0.5) ** 2 , n_dim=3, size_pop=100, max_iter=500, lb=[-1, -10, -5], ub=[2, 10, 2], precision=[1e-7, 1e-7, 1]) ga.register(operator_name='crossover', operator=crossover.crossover_2point_prob, crossover_prob=0.5) best_x, best_y = ga.run() print('best_x:', best_x, '\n', 'best_y:', best_y) — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#79 (comment) <#79 (comment)>>, or unsubscribe https://github.com/notifications/unsubscribe-auth/APF2ZCSG4VKXT7FJLXZACZDTVBT4JANCNFSM4RKQBE6Q . https://github.com/guofei9987/scikit-opt/blob/master/examples/demo_ga.py — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#79 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/APF2ZCWOVITL54TGS66AE4LTVW6SFANCNFSM4RKQBE6Q .

pip install --upgrade scikit-opt