差分进化算法代码python

# -*- coding: cp936 -*-
import numpy as np
import math
import random

class DE():
    def __init__(self,PN,dim,F,CR):
        self.F = F
        self.CR = CR
        self.x_max = 5.12
        self.x_min = -5.12
        self.PN = PN #种群数量
        self.dim = dim #基因个数
        self.fit = np.zeros(self.PN)
        self.X = np.zeros((self.PN,self.dim))
        self.V = np.zeros((self.PN,self.dim))
        self.U = np.zeros((self.PN, self.dim))

    # Rastrigr 函数
    def function(self,X):
        f = 0
        for i in range(0, len(X)):
            f = f + (X[i] ** 2 - (10 * math.cos(2 * np.pi * X[i])) + 10)
        return f
    
    #----------------------------初始化种群-------------------------------------
    def initpolulation(self):
        for i in range(self.PN):
            for j in range(self.dim):
                self.X[i][j] = self.x_max +random.random()*(self.x_max-self.x_min)

    # ----------------------------变异-------------------------------------
    def mutation(self):
        for i in range(self.PN):
            r1 = random.randint(0,self.PN-1)
            while i == r1:
                r1 = random.randint(0, self.PN - 1)
            r2 = random.randint(0, self.PN - 1)
            while i == r2 | r1 == r2:
                r2 = random.randint(0, self.PN - 1)
            r3 = random.randint(0, self.PN - 1)
            while i == r1 | r1 == r3 | r2 ==r3:
                r3 = random.randint(0, self.PN - 1)
            self.V[i] = self.X[r1] + self.F*(self.X[r2]-self.X[r3])

    # ----------------------------交叉-------------------------------------
    def cross(self):
        for i in range(self.PN):
            for j in range(self.dim):
                if (self.CR >= random.random()) | (j == random.randint(0,self.dim-1)):
                    self.U[i][j] = self.V[i][j]
                else:
                    self.U[i][j] = self.X[i][j]

    # ----------------------------选择-------------------------------------
    def select(self):
        for i in range(self.PN):
            if self.function(self.U[i]) <= self.function(self.X[i]):
                self.X[i] = self.U[i]
            else:
                self.X[i] = self.X[i]
            self.fit[i] = self.function(self.X[i])
        print(min(self.fit))
        return self.fit

if __name__ == '__main__':
    DE = DE(100,10,0.6,0.7)
    DE.initpolulation()
    for t in range(2000):
        DE.mutation()
        DE.cross()
        DE.select()

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