百度怎么发展起来的:求助fortran语言编写的混合遗传算法例子那位大哥大姐有？

#include<iostream.h>
#include<stdio.h>
#include<stdlib.h>
#include<math.h>
#define MaxGen 30
#define chrom_length 4
#define PopSize 20
#define Upper_Num 5
#define Down_Num 6
#define Point_Num 11
#define INFINITY 9999
#define pc 0.6
#define pm 0.05
#define E 2.78
double d=2,l=10;
double weight=0.5;
int gen;
struct individual{
int chrom[chrom_length];
double value;
double fitness;
};
struct Point{
double x;
double y;
}m_point[Point_Num]={{0,0},{d,0},{2*d,0},{3.5*d,0},{5*d,0},
{2*d,l},{3*d,l},{4*d,l},{0,l+d},{d,l+d},{5*d,l+d}};

double best=INFINITY;

int Best[chrom_length];

struct individual population[PopSize];

double Upper_Array[Upper_Num][35]={

4,3,2,3,4,4,3,1,3,4,2,1,0,1,2,3.5,5,17,15,15,14,12,13,13,15,9,10,11，12,13,13,11,13,10,12,5,4,3,4,5,5,4,2,2,3,3,2,1,0,1,2.5,4,16,14,14,13,11,12,12,14,8,9,10,11,12,12,10,12,9,11,6,5,4,5,4,6,5,3,3,2,4,3,2,1,0,1.5,3,15,13,13,17,10,11,11,13,7,8,9,10,11,11,9,11,8,10,

7.5,6.5,5.5,6.5,5.5,7.5,6.5,4.5,4.5,3.5,5.5,4.5,3.5,2.5,

1.5,0,1.5,13.5,11.5,11.5,10.5,8.5,9.5,9.5,11.5,5.5,6.5,7.5,8.5,9.5,9.5,7.5,9.5,6.5,8.5,9,8,7,6,5,9,8,6,6,5,7,6,5,4,3,1.5,0,12,10,10,9,7,8,8,10,4,5,6,7,8,8,6,8,5,7

};

double Down_Array[Down_Num][12]={

0,2,4,4,3,2,3,4,5,8.47214,8,6,

2,0,2,5,4,3,2,3,4,9.47214,9,7,

4,2,0,6,5,4,3,2,3,10.47214,10,8,

4,5,6,0,1,2,3,4,5,4.47214,4,2,
3,4,5,1,0,1,2,3,4,5.47214,5,3,
5,4,3,5,4,3,2,1,0,9.47214,9,7
};
int murr(int n){
int i,sum=1;
for(i=n;i>0;i--)
sum*=i;
return sum;
}
double min(double x,double y){
return (x>y?y:x);
}
double length(double x1,double y1,double x2,double y2){
return (sqrt(pow((x1-x2),2)+pow((y1-y2),2)));
}
double max(double x,double y){
return(x>y?x:y);
}
void Gener_Init(){//初始化
int i,j;
for(i=0;i<PopSize;i++)
{
do
{
for(j=0;j<chrom_length;j+=2)
population[i].chrom[j]=rand()%5;
}while(population[i].chrom[0]==population[i].chrom[2]);
do{
for(j=1;j<chrom_length;j+=2)
population[i].chrom[j]=rand()%6;
}while(population[i].chrom[1]==population[i].chrom[3]);
}
}
void Add_Value(){//目标函数
int i,j,t1,t2,t3,t4;
double Umin_Value,Dmin_Value;
double l1,l2;
for(i=0;i<PopSize;i++){
Umin_Value=0; Dmin_Value=0;
for(j=0;j<35;j++)
Umin_Value+=min(Upper_Array[population[i].chrom[0]][j],
Upper_Array[population[i].chrom[2]][j]);
for(j=0;j<12;j++)
Dmin_Value+=min(Down_Array[population[i].chrom[1]][j],
Down_Array[population[i].chrom[3]][j]);
t1=population[i].chrom[0];
t2=population[i].chrom[1]+5;
t3=population[i].chrom[2];
t4=population[i].chrom[3]+5;
l1=length(m_point[t1].x,
m_point[t1].y,
m_point[t2].x,
m_point[t2].y);
l2=length(m_point[t3].x,
m_point[t3].y,
m_point[t4].x,
m_point[t4].y);
population[i].value=weight*(Umin_Value+Dmin_Value)+(1-weight)*(l1+l2)*100;
}

}
void selection(){//选择
int i,index;
double p,temp=0,total=0;
double cfitness[PopSize];
struct individual newpopulation[PopSize];
for(i=0;i<PopSize;i++){
temp=max(population[i].value,temp);
total+=population[i].value;
}
temp+=100;
for(i=0;i<PopSize;i++){
population[i].fitness=(temp-population[i].value)/(PopSize*temp-total);
cfitness[i]=population[i].fitness;
}
for(i=1;i<PopSize;i++)
cfitness[i]+=cfitness[i-1];
for(i=0;i<PopSize;i++){
p=rand()%1000/1000.0;
index=0;
while(p>cfitness[index])
index++;
newpopulation[i]=population[index];
}
for(i=0;i<PopSize;i++){
population[i]=newpopulation[i];
}
}

void Crossing(){//

int i,j;//

int index[PopSize],temp,point;

double p;

for(i=0;i<PopSize;i++)

index[i]=i;

for(i=0;i<PopSize;i++){

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

temp=index[i];

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

index[point+i]=temp;

}

for(i=0;i<PopSize;i+=2){

p=rand()%1000/1000.0;

if(p<pc){

point=rand()%2;

if(point==0)

for(j=0;j<chrom_length;j+=2)

{

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

population[index[i]].chrom[j]

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

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

}

else

for(j=1;j<chrom_length;j+=2)

{

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

population[index[i]].chrom[j]

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

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

}

}

}

}

void Muta_Opeator(){//

int i,j,s,q;

double p;

for(i=0;i<PopSize;i++)

for(j=0;j<chrom_length;j++){

p=rand()%1000/1000.0;

if(p<pm){

q=rand()%4;

switch(q){

case 0:

s=rand()%5;

while(s==population[i].chrom[2])

s=rand()%5;

population[i].chrom[q]=s;

break;

case 1:

s=rand()%6;

while(s==population[i].chrom[3])

s=rand()%6;

population[i].chrom[q]=s;

break;

case 2:

s=rand()%5;

while(s==population[i].chrom[0])

s=rand()%5;

population[i].chrom[q]=s;

break;

case 3:

s=rand()%6;

while(s==population[i].chrom[1])

s=rand()%6;

population[i].chrom[q]=s;

break;

}

}

}

}

void print(){

int i,temp=-1;

double average,sum=0;

cout<<endl;

for(i=0;i<PopSize;i++)

sum+=population[i].value;

average=sum/PopSize;

for(i=0;i<PopSize;i++){

if(best>=population[i].value){

best=population[i].value;

temp=i;

}

}

if(temp!=-1){

for(i=0;i<chrom_length;i++)

Best[i]=population[temp].chrom[i];

}

cout<<"Generation="<<gen<<" Average="<<average

<<" Best_Value="<<best<<endl;

cout<<"Best_Chrom";

for(i=0;i<chrom_length;i++)

cout<<Best[i]<<" ";

cout<<endl;

}

void main(){

int q=5,k;

double p[35],sum;

int i,j;

do{

for(i=0;i<35;i++){

k=rand()%(3*q);

p[i]=pow(q,k)*pow(E,-1*q)/(murr(k));

sum+=p[i];}

}while(sum==1.0);

for(i=0;i<Upper_Num;i++)

for(j=0;j<35;j++)

Upper_Array[i][j]*=p[j];

do{

for(i=0;i<12;i++){

k=rand()%(3*q);

p[i]=pow(q,k)*pow(E,-1*q)/(murr(k));

sum+=p[i];}

}while(sum==1.0);

for(i=0;i<Down_Num;i++)

for(j=0;j<12;j++)

Down_Array[i][j]*=p[j];

gen=0;

Gener_Init();

while(gen<MaxGen){

Add_Value();

print();

selection();

Crossing();

Muta_Opeator();

// print();

gen++;

}

}