遗传算法matlab实现源程序

附页：

一．遗传算法源程序：

clc; clear; population; %评价目标函数值 for uim=1:popsize

vector=population(uim,:);

obj(uim)=hanshu(hromlength,vector,phen); end %obj %min(obj)

clear uim; objmin=min(obj); for sequ=1:popsize

if obj(sequ)==objmin

opti=population(sequ,:); end end clear sequ; fmax=22000; %==

for gen=1:maxgen %选择操作

%将求最小值的函数转化为适应度函数 for indivi=1:popsize

obj1(indivi)=1/obj(indivi); end

clear indivi; %适应度函数累加总合 total=0;

for indivi=1:popsize

total=total+obj1(indivi); end

clear indivi;

%每条染色体被选中的几率

for indivi=1:popsize

fitness1(indivi)=obj1(indivi)/total; end

clear indivi;

%各条染色体被选中的范围 for indivi=1:popsize fitness(indivi)=0; for j=1:indivi

fitness(indivi)=fitness(indivi)+fitness1(j); end end clear j; fitness;

%选择适应度高的个体 for ranseti=1:popsize ran=rand;

while (ran>1||ran<0) ran=rand; end ran;

if ran<=fitness(1)

newpopulation(ranseti,:)=population(1,:); else

for fet=2:popsize

if (ran>fitness(fet-1))&&(ran<=fitness(fet))

newpopulation(ranseti,:)=population(fet,:); end end end end clear ran; newpopulation; %交叉

for int=1:2:popsize-1

popmoth=newpopulation(int,:); popfath=newpopulation(int+1,:); popcross(int,:)=popmoth; popcross(int+1,:)=popfath; randnum=rand; if(randnum< P>

cpoint1=round(rand*hromlength); cpoint2=round(rand*hromlength); while (cpoint2==cpoint1) cpoint2=round(rand*hromlength); end

if cpoint1>cpoint2 tem=cpoint1; cpoint1=cpoint2; cpoint2=tem;