遗传算法+Python代码

算法原理

to-do

Python代码

# -- coding: utf-8 --

import numpy as np
import math

def solve_p(domain):
    N = 20
    domain = np.asarray(domain)
    temp = max(np.max(abs(domain),axis=0))
    p = (len(bin(temp))-2)*N
    return p

def randInit(p,num,paraNum):
    '''随机生成随机数'''
    xSum = [None]*paraNum
    for i in range(paraNum):
        x = [None]*num
        for j in range(num):
            temp = np.random.randint(0,2,p)
            x[j] = ''.join(str(temp[j]) for j in range(p))
        xSum[i] = x
    return xSum

def bin2dec(p,b,num,paraNum):
    maxNumBin = '1'*p
    maxNumDec = int(maxNumBin,2)
    d = [None]*paraNum
    for i in range(paraNum):
        temp = [None]*num
        for j in range(num):
            temp[j] = int(b[i][j],2)/maxNumDec
        d[i] = temp
    return d

def values(p,x,func,num,paraNum):
    x = bin2dec(p,x,num,paraNum) #转换为十进制
    v = [None]*num
    for j in range(num):
        temp = [None]*paraNum
        for i in range(paraNum):
            temp[i] = x[i][j]
        v[j] = func(temp)
    return v

def func(t):
    y = -20*math.exp(-0.2*math.sqrt(0.5*(t[0]**2+t[1]**2)))-math.exp(0.5*(math.cos(2*math.pi*t[0])+math.cos(2*math.pi*t[1])))+22.71282
#    y = t[0]**2+t[1]**2
    return y

def copy(x,v,num,paraNum):
    #轮盘赌算法
    v = np.asarray(v)/sum(v)
    cumV = [0]*num
    for i in range(num):
        cumV[i] = cumV[i-1] + v[i]

    someList = [y for y in range(num)]
    n = [0]*num
    for i in range(num):
        temp = np.random.random()
        for j in range(num):
            if temp < cumV[j]:
                n[j] += 1
                break
    #生成复制
    x2 = [None]*paraNum
    for i in range(paraNum):
        temp = [None]*num
        for j in range(num):
            temp[j] = x[i][j]
        x2[i] = temp
    return x2

def cross(x2,num,paraNum):
    x3 = [None]*paraNum
    flag = np.random.randint(0,num)
    s = np.random.permutation(num) #partnership
    for i in range(paraNum):
        temp = [None]*num
        for j in range(0,num-1,2):
            temp[s[j]],temp[s[j+1]] = x2[i][s[j]][:flag]+x2[i][s[j+1]][flag:],x2[i][s[j+1]][:flag]+x2[i][s[j]][flag:]
        for k in range(j+1,num):
            temp[s[k]] = x2[i][s[k]]
        x3[i] = temp
    return x3

def heter(x3,p,pro,num,paraNum):
    x4 = [None]*paraNum
    for i in range(paraNum):
        temp2 = [None]*num
        for j in range(num):
            temp = list(x3[i][j])
            for k in range(p):
                if np.random.random() < pro:
                    temp[k] = str((int(temp[k])+1)%2)
            temp2[j] = ''.join(temp)
        x4[i] = temp2
    return x4

def dieOut(x5,v2,num,paraNum):
    vS = list(enumerate(v2))
    def takeSecond(elem):
        return elem[1]
    vS.sort(key=takeSecond,reverse=True)
    xNext = [None]*paraNum
    for i in range(paraNum):
        temp = [None]*num
        for j in range(num):
            temp[j] = x[i][vS[j][0]]
        xNext[i] = temp
    return xNext

def out(p,x,num,paraNum):
    print('最优取值为：',end='')
    temp = [None]*paraNum
    for i in range(paraNum):
        temp[i] = bin2dec(p,x[i][0],1,1)
    print(temp)
    
    for j in range(paraNum):
        for i in range(paraNum):
            temp[i] = temp[i][0]
    print('最优解为',func(temp))


num = 50 #种群个数
paraNum = 2 #变量个数
domain = [[-5,5],[-5,5]] #定义域
p = solve_p(domain)
x = randInit(p,num,paraNum)
iterTimes = 50

for i in range(iterTimes):
    v = values(p,x,func,num,paraNum)
    x2 = copy(x,v,num,paraNum)
    x3 = cross(x2,num,paraNum)
    x4 = heter(x3,p,0.001,num,paraNum)
    v2 = values(p,x4,func,num,paraNum)
    x5 = x+x4
    x = dieOut(x5,v2,num,paraNum)
out(p,x,num,paraNum)