基本蚁群算法程序.txt

蚁群算法程序

//基本蚁群算法程序

//程序在vc++6.0下面同过，对原来的做了一点修改。
//你可以使用本代码，如果感到对你有用的话，请通知作者，作者会很高兴。
//通讯地址：[e-mail]
//by FashionXu
#include 
#include 
#include 
#include 
using namespace std;


const int iAntCount=34;//ant numbers
const int iCityCount=51;
const int iItCount=2000;
const double Q=100;
const double alpha=1;
const double beta=5;
const double rou=0.5;

int besttour[iCityCount];

double  rnd(int low,double uper)
{
 double p=(rand()/(double)RAND_MAX)*((uper)-(low))+(low);

 return (p);
};
int rnd(int uper)
{
 return (rand()%uper);
};

class GInfo
{
public: 
 double m_dDeltTrial[iCityCount][iCityCount];//信息素增量
 double m_dTrial[iCityCount][iCityCount];//信息素痕迹
 double distance[iCityCount][iCityCount];//距离
};


GInfo Map;
class ant
{
private:
 int ChooseNextCity();
 double prob[iCityCount];//转移概率
 int m_iCityCount;
 int AllowedCity[iCityCount];
public:
 void addcity(int city);
 int tabu[iCityCount];//行走路径
 void Clear();
 void UpdateResult();
 double m_dLength;
 double m_dShortest;
 void move();
 ant();
 void move2last();
};
void ant::move2last()
{
 int i;
 for(i=0;i  if (AllowedCity[i]==1)
  {
   addcity(i);
   break;
  }
}
void ant::Clear()
{
 m_dLength=0;
 int i;
 for(i=0;i {
  prob[i]=0;
  AllowedCity[i]=1;
 }
 i=tabu[iCityCount-1];
 m_iCityCount=0;
 addcity(i);
}
ant::ant()
{
 m_dLength=m_dShortest=0;
 m_iCityCount=0;
 int i;
 for(i=0;i {
  AllowedCity[i]=1;
  prob[i]=0;
 }
}
void ant::addcity(int city)
{
 //add city to tabu;
 tabu[m_iCityCount]=city;
 m_iCityCount++;
 AllowedCity[city]=0;
}
int ant::ChooseNextCity()
{
 //Update the probability of path selection
 //select a path from tabu[m_iCityCount-1] to next


 int i;
 int j=10000;
 double temp=0;
 int curCity=tabu[m_iCityCount-1];
 for (i=0;i 
{
  if((AllowedCity[i]==1)) 
  {
   temp+=pow((1.0/Map.distance[curCity][i]),beta)*pow((Map.m_dTrial[curCity][i]),alpha);
                          //距离                           //残留信息量
  }
 }
 double sel=0;
 for (i=0;i 
{  
  if((AllowedCity[i]==1))
  {
   prob[i]=pow((1.0/Map.distance[curCity][i]),beta)*pow((Map.m_dTrial[curCity][i]),alpha)/temp;
   sel+=prob[i];
  }
  else 
   prob[i]=0;
 }
 double mRate=rnd(0,sel);
 double mSelect=0;

 for ( i=0;i 
{  
  if((AllowedCity[i]==1))
   mSelect+=prob[i] ;
  if (mSelect>=mRate) 
  {j=i;break;}
 }

 if (j==10000)
 {
  temp=-1;
  for (i=0;i  
 { 
   if((AllowedCity[i]==1))
    if (temp    
   {
     temp=pow((1.0/Map.distance[curCity][i]),beta)*pow((Map.m_dTrial[curCity][i]),alpha);
     j=i;
    }
  }
 }

 return j;

}
void ant::UpdateResult()
{
 // Update the length of tour
 int i;
 for(i=0;i  m_dLength+=Map.distance[tabu[i]][tabu[i+1]];
 m_dLength+=Map.distance[tabu[iCityCount-1]][tabu[0]];
}
void ant::move()
{
 //the ant move to next town and add town ID to tabu.
 int j;
 j=ChooseNextCity();
 addcity(j);
}
class project
{
public:

 void UpdateTrial();
 double m_dLength;
 void initmap();
 ant ants[iAntCount];
 void GetAnt();
 void StartSearch();
 project();
};
void project::UpdateTrial()
{
 //calculate the changes of trial information
 int i;
 int j;

 for(i=0;i {
  for (j=0;j  {
   Map.m_dDeltTrial[ants[i].tabu[j]][ants[i].tabu[j+1]]+=Q/ants[i].m_dLength ;
   Map.m_dDeltTrial[ants[i].tabu[j+1]][ants[i].tabu[j]]+=Q/ants[i].m_dLength;
  }
  Map.m_dDeltTrial[ants[i].tabu[iCityCount-1]][ants[i].tabu[0]]+=Q/ants[i].m_dLength;
  Map.m_dDeltTrial[ants[i].tabu[0]][ants[i].tabu[iCityCount-1]]+=Q/ants[i].m_dLength;
 }
 for (i=0;i {
  for (j=0;j  {
   Map.m_dTrial[i][j]=(rou*Map.m_dTrial[i][j]+Map.m_dDeltTrial[i][j] );
   Map.m_dDeltTrial[i][j]=0;
  }

 }


}
void project::initmap()
{
 int i;
 int j;
 for(i=0;i  for (j=0;j  {

   Map.m_dTrial[i][j]=1;
   Map.m_dDeltTrial[i][j]=0;
  }
}
project::project()
{
 //initial map,read map infomation from file . et.
 initmap();
 m_dLength=10e9;


 ifstream in("eil51.tsp");

 struct city
 {
  int num;
  int x;
  int  y;
 }cc[iCityCount];
 
 for (int i=0;i 
 {
  in>>cc[i].num>>cc[i].x>>cc[i].y;
  besttour[i]=0;
 }
 int j;
 for(i=0;i  for (j=0;j  
 {
   {
    Map.distance[i][j]=sqrt(pow((cc[i].x-cc[j].x),2)+pow((cc[i].y-cc[j].y),2));
   }
 }


}
void project::GetAnt()
{
 //randomly put ant into map
 int i=0;
 int city;
 srand( (unsigned)time( NULL ) +rand());
 for (i=0;i {
  city=rnd(iCityCount);
  ants[i].addcity(city);
 }

}
void project::StartSearch()
{
 //begin to find best solution
 int max=0;//every ant tours times
 int i;
 int j;
 double temp;
 int temptour[iCityCount];
 while (max 
{  
  for(j=0;j

  { 
   for (i=0;i    ants[j].move();
  }

  for(j=0;j  
 {
   ants[j].move2last();
   ants[j].UpdateResult ();
  }

  //find out the best solution of the step and put it into temp
  int t;
  temp=ants[0].m_dLength;
  for (t=0;t   
  temptour[t]=ants[0].tabu[t];
  for(j=0;j  
 {
   if (temp>ants[j].m_dLength) 
   {
    temp=ants[j].m_dLength;
    for ( t=0;t     temptour[t]=ants[j].tabu[t];
   }

  }

  if(temp   
  m_dLength=temp;
   for ( t=0;t
  {
   besttour[t]=temptour[t];
  }
  printf("%d : %f\n",max,m_dLength);
  UpdateTrial(); 

  for(j=0;j   ants[j].Clear();

  max++;

 }
 printf("The shortest toure is : %f\n",m_dLength);

 for ( int t=0;t  printf(" %d ",besttour[t]);

}
int main()
{

 project TSP;
 TSP.GetAnt();
 TSP.StartSearch();
 return 0;
}