遗传算法C语言源代码一元函数和二元函数.docx
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遗传算法C语言源代码一元函数和二元函数
C语言遗传算法代码
以下为遗传算法的源代码,计算一元代函数的代码和二元函数的代码以+++++++++++++++++++++++++++++++++++++为分割线分割开来,请自行选择适合的代码,使用时请略看完代码的注释,在需要更改的地方更改为自己需要的代码。
+++++++++++++++++++++++++++++++一元函数代码++++++++++++++++++++++++++++
#include
#include
#include
#include
#definePOPSIZE1000
#definemaximization1
#defineminimization2
#definecmax100
#definecmin0
#definelength120
#definechromlengthlength1//染色体长度
//注意,你是求最大值还是求最小值
intfunctionmode=minimization;
//变量的上下限的修改开始
floatmin_x1=-2;//变量的下界
floatmax_x1=-1;//变量的上界
//变量的上下限的修改结束
intpopsize;//种群大小
intmaxgeneration;//最大世代数
doublepc;//交叉率
doublepm;//变异率
structindividual
{
charchrom[chromlength+1];
doublevalue;
doublefitness;//适应度
};
intgeneration;//世代数
intbest_index;
intworst_index;
structindividualbestindividual;//最佳个体
structindividualworstindividual;//最差个体
structindividualcurrentbest;
structindividualpopulation[POPSIZE];
//函数声明
voidgenerateinitialpopulation();
voidgeneratenextpopulation();
voidevaluatepopulation();
longdecodechromosome(char*,int,int);
voidcalculateobjectvalue();
voidcalculatefitnessvalue();
voidfindbestandworstindividual();
voidperformevolution();
voidselectoperator();
voidcrossoveroperator();
voidmutationoperator();
voidinput();
voidoutputtextreport();
voidgenerateinitialpopulation()//种群初始化
{
inti,j;
for(i=0;i{
for(j=0;j{
population[i].chrom[j]=(rand()%20<10)?
'0':
'1';
}
population[i].chrom[chromlength]='\0';
}
}
voidgeneratenextpopulation()//生成下一代
{
selectoperator();
crossoveroperator();
mutationoperator();
}
voidevaluatepopulation()//评价个体,求最佳个体
{
calculateobjectvalue();
calculatefitnessvalue();
findbestandworstindividual();
}
longdecodechromosome(char*string,intpoint,intlength)//给染色体解码
{
inti;
longdecimal=0;
char*pointer;
for(i=0,pointer=string+point;iif(*pointer-'0')
{decimal+=(long)pow(2,i);
}
return(decimal);
}
voidcalculateobjectvalue()//计算函数值
{
inti;
longtemp1,temp2;
doublex1;
for(i=0;i{
temp1=decodechromosome(population[i].chrom,0,length1);
x1=(max_x1-min_x1)*temp1/(1024*1024-1)+min_x1;
//目标函数修改开始
population[i].value=(pow(x1,5)-3*x1-1)*(pow(x1,5)-3*x1-1);
//目标函数修改结束
}
}
voidcalculatefitnessvalue()//计算适应度
{
inti;
doubletemp;
for(i=0;i{
if(functionmode==maximization)
{if((population[i].value+cmin)>0.0)
{temp=cmin+population[i].value;}
else
{temp=0.0;
}
}
elseif(functionmode==minimization)
{
if(population[i].value{temp=cmax-population[i].value;}
else{temp=0.0;}
}
population[i].fitness=temp;
}
}
voidfindbestandworstindividual()//求最佳个体和最差个体
{
inti;
doublesum=0.0;
bestindividual=population[0];
worstindividual=population[0];
for(i=1;iif(population[i].fitness>bestindividual.fitness){
bestindividual=population[i];
best_index=i;
}
elseif(population[i].fitness{
worstindividual=population[i];
worst_index=i;
}
sum+=population[i].fitness;
}
if(generation==0){
currentbest=bestindividual;
}
else{
if(bestindividual.fitness>=currentbest.fitness){
currentbest=bestindividual;
}
}
}
voidperformevolution()//演示评价结果
{
if(bestindividual.fitness>currentbest.fitness){
currentbest=population[best_index];
}
else{
population[worst_index]=currentbest;
}
}
voidselectoperator()//比例选择算法
{
inti,index;
doublep,sum=0.0;
doublecfitness[POPSIZE];
structindividualnewpopulation[POPSIZE];
for(i=0;i{sum+=population[i].fitness;}
for(i=0;icfitness[i]=population[i].fitness/sum;
}
for(i=1;icfitness[i]=cfitness[i-1]+cfitness[i];
}
for(i=0;i{
p=rand()%1000/1000.0;
index=0;
while(p>cfitness[index])
{
index++;
}
newpopulation[i]=population[index];
}
for(i=0;ipopulation[i]=newpopulation[i];
}
}
voidcrossoveroperator()//交叉算法
{
inti,j;
intindex[POPSIZE];
intpoint,temp;
doublep;
charch;
for(i=0;iindex[i]=i;
}
for(i=0;ipoint=rand()%(popsize-i);
temp=index[i];
index[i]=index[point+i];
index[point+i]=temp;
}
for(i=0;ip=rand()%1000/1000.0;
if(ppoint=rand()%(chromlength-1)+1;
for(j=point;jch=population[index[i]].chrom[j];
population[index[i]].chrom[j]=population[index[i+1]].chrom[j];
population[index[i+1]].chrom[j]=ch;
}
}
}
}
voidmutationoperator()//变异操作
{
inti,j;
doublep;
for(i=0;ifor(j=0;jp=rand()%1000/1000.0;
if(ppopulation[i].chrom[j]=(population[i].chrom[j]=='0')?
'1':
'0';
}
}
}
}
voidinput()//数据输入
{//printf("初始化全局变量:
\n");
//printf("种群大小(50-500):
");
//scanf("%d",&popsize);
popsize=500;
if((popsize%2)!
=0)
{
//printf("种群大小已设置为偶数\n");
popsize++;};
//printf("最大世代数(100-300):
");
//scanf("%d",&maxgeneration);
maxgeneration=200;
//printf("交叉率(0.2-0.99):
");
//scanf("%f",&pc);
pc=0.95;
//printf("变异率(0.001-0.1):
");
//scanf("%f",&pm);
pm=0.03;
}
voidoutputtextreport()//数据输出
{
inti;
doublesum;
doubleaverage;
sum=0.0;
for(i=0;i{sum+=population[i].value;}
average=sum/popsize;
printf("当前世代=%d\n当前世代平均函数值=%f\n当前世代最优函数值=%f\n",generation,average,population[best_index].value);
}
voidmain()//主函数
{inti;
longtemp1,temp2;
doublex1,x2;
generation=0;
input();
generateinitialpopulation();
evaluatepopulation();
while(generation{
generation++;
generatenextpopulation();
evaluatepopulation();
performevolution();
outputtextreport();
}
printf("\n");
printf("统计结果:
");
printf("\n");
//printf("最大函数值等于:
%f\n",currentbest.fitness);
printf("其染色体编码为:
");
for(i=0;i{
printf("%c",currentbest.chrom[i]);
}
printf("\n");
temp1=decodechromosome(currentbest.chrom,0,length1);
x1=(max_x1-min_x1)*temp1/(1024*1024-1)+min_x1;
printf("x1=%lf\n",x1);
//这是需要修改的地方
printf("最优值等于:
%f\n",(pow(x1,5)-3*x1-1)*(pow(x1,5)-3*x1-1));
}
+++++++++++++++++++++++++二元函数代码+++++++++++++++++++++++++++++++++++++++++
#include
#include
#include
#include
#definePOPSIZE500
#definemaximization1
#defineminimization2
#definecmax100
#definecmin0
#definelength120
#definelength220
#definechromlengthlength1+length2//染色体长度
//-----------求最大还是最小值
intfunctionmode=maximization;
//-----------
//-----------变量上下界
floatmin_x1=0;
floatmax_x1=3;
floatmin_x2=1;
floatmax_x2=5;
//-----------
intpopsize;//种群大小
intmaxgeneration;//最大世代数
doublepc;//交叉率
doublepm;//变异率
structindividual
{
charchrom[chromlength+1];
doublevalue;
doublefitness;//适应度
};
intgeneration;//世代数
intbest_index;
intworst_index;
structindividualbestindividual;//最佳个体
structindividualworstindividual;//最差个体
structindividualcurrentbest;
structindividualpopulation[POPSIZE];
//函数声明
voidgenerateinitialpopulation();
voidgeneratenextpopulation();
voidevaluatepopulation();
longdecodechromosome(char*,int,int);
voidcalculateobjectvalue();
voidcalculatefitnessvalue();
voidfindbestandworstindividual();
voidperformevolution();
voidselectoperator();
voidcrossoveroperator();
voidmutationoperator();
voidinput();
voidoutputtextreport();
voidgenerateinitialpopulation()//种群初始化
{
inti,j;
for(i=0;i{
for(j=0;j{
population[i].chrom[j]=(rand()%40<20)?
'0':
'1';
}
population[i].chrom[chromlength]='\0';
}
}
voidgeneratenextpopulation()//生成下一代
{
selectoperator();
crossoveroperator();
mutationoperator();
}
voidevaluatepopulation()//评价个体,求最佳个体
{
calculateobjectvalue();
calculatefitnessvalue();
findbestandworstindividual();
}
longdecodechromosome(char*string,intpoint,intlength)//给染色体解码
{
inti;
longdecimal=0;
char*pointer;
for(i=0,pointer=string+point;iif(*pointer-'0')
{decimal+=(long)pow(2,i);
}
return(decimal);
}
voidcalculateobjectvalue()//计算函数值
{
inti;
longtemp1,temp2;
doublex1,x2;
for(i=0;i{
temp1=decodechromosome(population[i].chrom,0,length1);
temp2=decodechromosome(population[i].chrom,length1,length2);
x1=(max_x1-min_x1)*temp1/(1024*1024-1)+min_x1;
x2=(max_x2-min_x2)*temp2/(1024*1024-1)+min_x2;
//-----------函数
population[i].value=x1*x1+sin(x1*x2)-x2*x2;
//-----------
}
}
voidcalculatefitnessvalue()//计算适应度
{
inti;
doubletemp;
for(i=0;i{
if(functionmode==maximization)
{if((population[i].value+cmin)>0.0)
{temp=cmin+population[i].value;}
else
{temp=0.0;
}
}
elseif(functionmode==minimization)
{
if(population[i].value{temp=cmax-population[i].value;}
else{temp=0.0;}
}
population[i].fitness=temp;
}
}
voidfindbestandworstindividual()//求最佳个体和最差个体
{
inti;
doublesum=0.0;
bestindividual=population[0];
worstindividual=population[0];
for(i=1;iif(population[i].fitness>bestindividual.fitness){
bestindividual=population[i];
best_index=i;
}
elseif(population[i].fitness{
worstindividual=population[i];
worst_index=i;
}
sum+=population[i].fitness;
}
if(generation==0){
currentbest=bestindividual;
}
else{
if(bestindividual.fitness>=currentbest.fitness){
currentbest=bestindividual;
}
}
}
voidperformevolution()//演示评价结果
{
if(bestindividual.fitness>currentbest.fitness){
currentbest=population[best_index];
}
else{
population[wor