DEAP：按适合度对个人进行排序

Question

在评估了每个人的适应度之后，按个体适应度对总体进行分类的最佳方法是什么？

我手动实现了排序功能，但是也许有内置的方法可以做到这一点？

import random
from deap import base, tools, creator, algorithms

def sort(population):
    for i in range(len(population)):
        argmin = i
        minimum = population[i].fitness

        for j in range(i + 1, len(population)):
            if population[j].fitness < minimum:
                argmin = j

        population[argmin], population[i] = population[i], population[argmin]

    return population

def fitness(individual):
    return sum(individual),

toolbox = base.Toolbox()

creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", list, fitness=creator.FitnessMax)
toolbox.register("individual", tools.initRepeat, creator.Individual, random.random, n=2)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)

pop = toolbox.population(n=10)
fitnesses = toolbox.map(toolbox.evaluate, pop)
for ind, fit in zip(pop, fitnesses):
    ind.fitness.values = fit

print("Before")
for ind in pop:
    print(ind, ind.fitness)
pop = sort(pop)
print("After")
for ind in pop:
    print(ind, ind.fitness)

Answer 1

可以简单地使用Python内置函数

pop.sort(key=lambda x: x.fitness, reverse=True)

这会根据个人的健康状况将人口分类。