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

#define POPSIZE 1000

#define maximization 1

#define minimization 2

#define cmax 100

#define cmin 0

#define length1 20

#define chromlength length1 //染色体长度

//注意，你是求最大值还是求最小值

int functionmode=minimization;

//变量的上下限的修改开始

float min_x1=-2;//变量的下界

float max_x1=-1;//变量的上界

//变量的上下限的修改结束

int popsize; //种群大小

int maxgeneration; //最大世代数

double pc; //交叉率

double pm; //变异率

struct individual

{

char chrom[chromlength+1];

double value;

double fitness; //适应度

};

int generation; //世代数

int best_index;

int worst_index;

struct individual bestindividual; //最佳个体

struct individual worstindividual; //最差个体

struct individual currentbest;

struct individual population[POPSIZE];

//函数声明

void generateinitialpopulation();

void generatenextpopulation();

void evaluatepopulation();

long decodechromosome(char *,int,int);

void calculateobjectvalue();

void calculatefitnessvalue();

void findbestandworstindividual();

void performevolution();

void selectoperator();

void crossoveroperator();

void mutationoperator();

void input();

void outputtextreport();

void generateinitialpopulation( ) //种群初始化

{

int i,j;

for (i=0;i

{

for(j=0;j

{

population[i].chrom[j]=(rand()%20<10)?'0':'1';

}

population[i].chrom[chromlength]='\0';

}

}

void generatenextpopulation() //生成下一代

{

selectoperator();

crossoveroperator();

mutationoperator();

}

void evaluatepopulation() //评价个体，求最佳个体{

calculateobjectvalue();

calculatefitnessvalue();

findbestandworstindividual();

}

long decodechromosome(char *string ,int point,int length) //给染色体解码{

int i;

long decimal=0;

char*pointer;

for(i=0,pointer=string+point;i

if(*pointer-'0')

{decimal +=(long)pow(2,i);

}

return (decimal);

}

void calculateobjectvalue() //计算函数值

{

int i;

long temp1,temp2;

double x1;

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

}

}

void calculatefitnessvalue()//计算适应度

{

int i;

double temp;

for(i=0;i

{

if(functionmode==maximization)

{if((population[i].value+cmin)>0.0)

{temp=cmin+population[i].value;}

else

{temp=0.0;

}

}

else if (functionmode==minimization)

{

if(population[i].value

{temp=cmax-population[i].value;}

else{ temp=0.0;}

}

population[i].fitness=temp;

}

}

void findbestandworstindividual( ) //求最佳个体和最差个体{

int i;

double sum=0.0;

bestindividual=population[0];

worstindividual=population[0];

for (i=1;i

if (population[i].fitness>bestindividual.fitness){

bestindividual=population[i];

best_index=i;

}

else if (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;

}

}

}

void performevolution() //演示评价结果

{

if (bestindividual.fitness>currentbest.fitness){ currentbest=population[best_index];

}

else{

population[worst_index]=currentbest;

}

}

void selectoperator() //比例选择算法

{

int i,index;

double p,sum=0.0;

double cfitness[POPSIZE];

struct individual newpopulation[POPSIZE];

for(i=0;i

{sum+=population[i].fitness;}

for(i=0;i

cfitness[i]=population[i].fitness/sum;

}

for(i=1;i

cfitness[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;i

population[i]=newpopulation[i];

}

}

void crossoveroperator() //交叉算法

{

int i,j;

int index[POPSIZE];

int point,temp;

double p;

char ch;

for (i=0;i

index[i]=i;

}

for (i=0;i

point=rand()%(popsize-i);

temp=index[i];

index[i]=index[point+i];

index[point+i]=temp;

}

for (i=0;i

p=rand()%1000/1000.0;

if (p

point=rand()%(chromlength-1)+1;

for (j=point; j

ch=population[index[i]].chrom[j];

population[index[i]].chrom[j]=population[index[i+1]].chrom[j];

population[index[i+1]].chrom[j]=ch;

}

}

}

}

void mutationoperator() //变异操作

{

int i,j;

double p;

for (i=0;i

for(j=0;j

p=rand()%1000/1000.0;

if (p

population[i].chrom[j]=(population[i].chrom[j]=='0')?'1':'0';

}

}

}

void input() //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;

}

void outputtextreport()//数据输出

{

int i;

double sum;

double average;

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);

}

void main() //主函数

{ int i;

long temp1,temp2;

double x1,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

#define POPSIZE 500

#define maximization 1

#define minimization 2

#define cmax 100

#define cmin 0

#define length1 20

#define length2 20

#define chromlength length1+length2 //染色体长度

//-----------求最大还是最小值

int functionmode=maximization;

//-----------

//-----------变量上下界

float min_x1=0;

float max_x1=3;

float min_x2=1;

float max_x2=5;

//-----------

int popsize; //种群大小

int maxgeneration; //最大世代数

double pc; //交叉率

double pm; //变异率

struct individual

{

char chrom[chromlength+1];

double value;

double fitness; //适应度

};

int generation; //世代数

int best_index;

int worst_index;

struct individual bestindividual; //最佳个体struct individual worstindividual; //最差个体struct individual currentbest;

struct individual population[POPSIZE];

//函数声明

void generateinitialpopulation();

void generatenextpopulation();

void evaluatepopulation();

long decodechromosome(char *,int,int);

void calculateobjectvalue();

void calculatefitnessvalue();

void findbestandworstindividual();

void performevolution();

void selectoperator();

void crossoveroperator();

void mutationoperator();

void input();

void outputtextreport();

void generateinitialpopulation( ) //种群初始化{

int i,j;

for (i=0;i

{

for(j=0;j

{

population[i].chrom[j]=(rand()%40<20)?'0':'1';

}

population[i].chrom[chromlength]='\0';

}

}

void generatenextpopulation() //生成下一代

{

selectoperator();

crossoveroperator();

mutationoperator();

}

void evaluatepopulation() //评价个体，求最佳个体

{

calculateobjectvalue();

calculatefitnessvalue();

findbestandworstindividual();

}

long decodechromosome(char *string ,int point,int length) //给染色体解码{

int i;

long decimal=0;

char*pointer;

for(i=0,pointer=string+point;i

if(*pointer-'0')

{decimal +=(long)pow(2,i);

}

return (decimal);

}

void calculateobjectvalue() //计算函数值

{

int i;

long temp1,temp2;

double x1,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;

//-----------

}

}

void calculatefitnessvalue()//计算适应度

{

int i;

double temp;

for(i=0;i

{

if(functionmode==maximization)

{if((population[i].value+cmin)>0.0)

{temp=cmin+population[i].value;}

else

{temp=0.0;

}

}

else if (functionmode==minimization)

{

if(population[i].value

{temp=cmax-population[i].value;}

else{ temp=0.0;}

}

population[i].fitness=temp;

}

}

void findbestandworstindividual( ) //求最佳个体和最差个体{

int i;

double sum=0.0;

bestindividual=population[0];

worstindividual=population[0];

for (i=1;i

if (population[i].fitness>bestindividual.fitness){

bestindividual=population[i];

best_index=i;

}

else if (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;

}

}

}

void performevolution() //演示评价结果

{

if (bestindividual.fitness>currentbest.fitness){

currentbest=population[best_index];

}

else{

population[worst_index]=currentbest;

}

}

void selectoperator() //比例选择算法

{

int i,index;

double p,sum=0.0;

double cfitness[POPSIZE];

struct individual newpopulation[POPSIZE];

for(i=0;i

{sum+=population[i].fitness;}

for(i=0;i

cfitness[i]=population[i].fitness/sum;

}

for(i=1;i

cfitness[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;i

population[i]=newpopulation[i];

}

}

void crossoveroperator() //交叉算法

{

int i,j;

int index[POPSIZE];

int point,temp;

double p;

char ch;

for (i=0;i

index[i]=i;

}

for (i=0;i

point=rand()%(popsize-i);

temp=index[i];

index[i]=index[point+i];

index[point+i]=temp;

}

for (i=0;i

p=rand()%1000/1000.0;

if (p

point=rand()%(chromlength-1)+1;

for (j=point; j

ch=population[index[i]].chrom[j];

population[index[i]].chrom[j]=population[index[i+1]].chrom[j];

population[index[i+1]].chrom[j]=ch;

}

}

}

}

void mutationoperator() //变异操作

{

int i,j;

double p;

for (i=0;i

for(j=0;j

p=rand()%1000/1000.0;

if (p

population[i].chrom[j]=(population[i].chrom[j]=='0')?'1':'0';

}

}

}

}

void input() //数据输入

{ //printf("初始化全局变量:\n");

//printf(" 种群大小(50-500)：");

//scanf("%d", &popsize);

popsize=200;

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=0.9;

//printf(" 变异率(0.001-0.1)：");

//scanf("%f", &pm);

pm=0.003;

}

void outputtextreport()//数据输出

{

int i;

double sum;

double average;

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);

}

void main() //主函数

{ int i;

long temp1,temp2;

double x1,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);

temp2=decodechromosome(currentbest.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;

printf("x=%lf,y=%lf\n",x1,x2);

//-----------修改函数

printf("最大值=%f\n",x1*x1+sin(x1*x2)-x2*x2);

//-----------

}