【0-1背包问题】遗传算法 python 完整代码可直接运行

1.导入所需要的库

import numpy as np
import matplotlib.pyplot as plt

2.初始化

#初始化种群,popsize代表种群个数，n代表基因长度，
def init(popsize,n):
    population=[]
    for i in range(popsize):
        pop=''
        for j in range(n):

            pop=pop+str(np.random.randint(0,2))
        population.append(pop)
    return population

3.计算fitness

#计算种群中重量和效益
def computeFitness(population,weight,profit):
    total_weight = []
    total_profit = []
    for pop in population:
        weight_temp = 0
        profit_temp = 0
        for index in range(len(pop)):
            if pop[index] == '1':
                weight_temp += int(weight[index])
                profit_temp += int(profit[index])
        total_weight.append(weight_temp)
        total_profit.append(profit_temp)
    return  total_weight,total_profit
#计算单个个体
def computesingle(single,profit):
    profit_temp = 0
    for index in range(len(single)):
        if single[index] == '1':
            profit_temp += int(profit[index])
    return profit_temp

4.筛选

#筛选符合条件的
def select(population,weight_limit,total_weight,total_profit):
    w_temp = []
    p_temp = []
    pop_temp = []
    for weight in total_weight:
        out = total_weight.index(weight)
        if weight <= weight_limit:
            w_temp.append(total_weight[out])
            p_temp.append(total_profit[out])
            pop_temp.append(population[out])
    return pop_temp,w_temp,p_temp

4.轮盘赌选择

def roulettewheel(s_pop,total_profit):

    p =[0]
    temp = 0

    sum_profit = sum(total_profit)
    for i in range(len(total_profit)):

        unit = total_profit[i]/sum_profit
        p.append(temp+unit)
        temp += unit
    new_population = []
    i0 = 0
    while i0 < popsize:
        select_p = np.random.uniform()
        for i in range(len(s_pop)):

            if select_p