//基本蟻群算法的C++源程序

//程序在vc++6.0下面同過，對原來的做了一點修改。
//你可以使用本代碼，如果感到對你有用的話，請通知作者，作者會很高興。
//通訊地址：fashionxu@163.com
//by FashionXu
#include <iostream>
#include <fstream>
#include <math.h>
#include <time.h>
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];
?double m_dTrial[iCityCount][iCityCount];
?double distance[iCityCount][iCityCount];
};

GInfo Map;
class ant
{
private:
?int ChooseNextCity();
?double prob[iCityCount];
?int m_iCityCount;
?int AllowedCity[iCityCount];
public:
?void addcity(int city);
?int tabu[iCityCount];
?void Clear();
?void UpdateResult();
?double m_dLength;
?double m_dShortest;
?void move();
?ant();
?void move2last();
};
void ant::move2last()
{
?int i;
?for(i=0;i<iCityCount;i++)
??if (AllowedCity[i]==1)
??{
???addcity(i);
???break;
??}
}
void ant::Clear()
{
?m_dLength=0;
?int i;
?for(i=0;i<iCityCount;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<iCityCount;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<iCityCount;i++)
?{
??if((AllowedCity[i]==1))?
??{
???temp+=pow((1.0/Map.distance[curCity][i]),beta)*pow((Map.m_dTrial[curCity][i]),alpha);
??}
?}
?double sel=0;
?for (i=0;i<iCityCount;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<iCityCount;i++)
?{
??if((AllowedCity[i]==1))
???mSelect+=prob[i] ;
??if (mSelect>=mRate) {j=i;break;}
?}

?if (j==10000)
?{
??temp=-1;
??for (i=0;i<iCityCount;i++)
??{?
???if((AllowedCity[i]==1))
????if (temp<pow((1.0/Map.distance[curCity][i]),beta)*pow((Map.m_dTrial[curCity][i]),alpha))????
????{
?????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<iCityCount-1;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<iAntCount;i++)
?{
??for (j=0;j<iCityCount-1;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<iCityCount;i++)
?{
??for (j=0;j<iCityCount;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<iCityCount;i++)
??for (j=0;j<iCityCount;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<iCityCount;i++)
?{
??in>>cc[i].num>>cc[i].x>>cc[i].y;
??besttour[i]=0;
?}
?int j;
?for(i=0;i<iCityCount;i++)
??for (j=0;j<iCityCount;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<iAntCount;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<iItCount)
?{??
??for(j=0;j<iAntCount;j++)

??{
???for (i=0;i<iCityCount-1;i++)
????ants[j].move();
??}

??for(j=0;j<iAntCount;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<iCityCount;t++)
???temptour[t]=ants[0].tabu[t];
??for(j=0;j<iAntCount;j++)
??{
???if (temp>ants[j].m_dLength) {
????temp=ants[j].m_dLength;
????for ( t=0;t<iCityCount;t++)
?????temptour[t]=ants[j].tabu[t];
???}

??}

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

??for(j=0;j<iAntCount;j++)
???ants[j].Clear();

??max++;

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

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

}
int main()
{

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

求eil51最優到了438，可以修改循環次數和其他參數。以得到更好的解。使用TSP數據的時候，將前面的一些字符串信息刪除，只留下坐標數據。