如何在基于DEAP的Python遗传算法中添加消除机制 [英] How to add elimination mechanism in Python genetic algorithm based on DEAP

问题描述

这是我的问题.
我正在使用DEAP处理一个优化问题.

Here is my question.
I'm dealing with one optimization problem using DEAP.

目前，我使用toolbox.register("select", tools.selNSGA2)选择一些最适合自己的人生存.

For now, I use toolbox.register("select", tools.selNSGA2) to select some fittest indivual to survive.

但是我想通过用户定义的函数添加一些阈值.

But I want to add some threshold by user-defined function.

算法可以实现两步选择吗?

Can the algorithm achieve two step of selection?

1. 通过锦标赛或selNSGA2方法选择几个人

1. Select several individuals by the tournament or selNSGA2 method

通过预定义的阈值消除多个人.

Eliminate several individuals by pre-defined thresholds.

推荐答案

这应该有效.

def myselect(pop, k, check):
    return [ind for in in tools.selNSGA2(pop, k) if check(ind)]

def mycheck(ind):
    return True

toolbox.register("select", myselect, check=mycheck)

但是，您最终将选择< = k个后代.

However, you will end up selecting <= k offspring.

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