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遗传算法源程序

关键词： 遗传算法    源程序    数学模型                                          

遗传算法源程序附件：

#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++;

   }

}

【作者: xixiawen】【访问统计:】【2005年12月10日 星期六 15:43】【 加入博采】【打印】