蚁群算法代码

//Basic Ant Colony Algorithm for TSP#include <iostream.h>#include <fstream.h>#include <math.h>#include <time.h>#include <conio.h>#include <stdlib.h>#include <iomanip.h>#define N 31 //city size#define M 31 //ant numberdouble inittao=1;double tao[N][N];double detatao[N][N];double distance[N][N];double yita[N][N];int tabu[M][N];int route[M][N];double solution[M];int BestRoute[N];double BestSolution=10000000000;double alfa,beta,rou,Q;int NcMax;void initparameter(void); // initialize the parameters of basic ACAdouble EvalueSolution(int *a); // evaluate the solution of TSP, and calculate the length of path void InCityXY( double x[], double y[], char *infile ); // input the nodes' coordinates of TSPvoid initparameter(void){alfa=1; beta=5; rou=0.9; Q=100;NcMax=200;}void main(void){int NC=0;initparameter();double x[N];double y[N];InCityXY( x, y, "city31.tsp" );for(int i=0;i<N;i++)for(int j=i+1;j<N;j++){distance[j][i]=sqrt((x[i]-x[j])*(x[i]-x[j])+(y[i]-y[j])*(y[i]-y[j])); distance[i][j]=distance[j][i];}// calculate the heuristic parametersfor(i=0;i<N;i++)for(int j=0;j<N;j++){tao[i][j]=inittao;if(j!=i)yita[i][j]=100/distance[i][j];}for(int k=0;k<M;k++)for(i=0;i<N;i++)route[k][i]=-1;srand(time(NULL));for(k=0;k<M;k++){route[k][0]=k%N;tabu[k][route[k][0]]=1;}//each ant try to find the optiamal pathdo {int s=1;double partsum;double pper;double drand;//ant choose one whole pathwhile(s<N){for(k=0;k<M;k++){int jrand=rand()%3000;drand=jrand/3001.;partsum=0;pper=0;for(int j=0;j<N;j++){if(tabu[k][j]==0)partsum+=pow(tao[route[k][s-1]][j],alfa)*pow(yita[route[k][s-1]][j],beta); }for(j=0;j<N;j++){if(tabu[k][j]==0)pper+=pow(tao[route[k][s-1]][j],alfa)*pow(yita[route[k][s-1]][j],beta)/partsum; if(pper>drand)break;}tabu[k][j]=1;route[k][s]=j;}s++;}// the pheromone is updatedfor(i=0;i<N;i++)for(int j=0;j<N;j++)detatao[i][j]=0;for(k=0;k<M;k++){solution[k]=EvalueSolution(route[k]);if(solution[k]<BestSolution){BestSolution=solution[k];for(s=0;s<N;s++)BestRoute[s]=route[k][s];}}for(k=0;k<M;k++){for(s=0;s<N-1;s++)detatao[route[k][s]][route[k][s+1]]+=Q/solution[k];detatao[route[k][N-1]][route[k][0]]+=Q/solution[k];}for(i=0;i<N;i++)for(int j=0;j<N;j++){tao[i][j]=rou*tao[i][j]+detatao[i][j];if(tao[i][j]<0.00001)tao[i][j]=0.00001;if(tao[i][j]>20)tao[i][j]=20;}for(k=0;k<M;k++)for(int j=1;j<N;j++){tabu[k][route[k][j]]=0;route[k][j]=-1;}NC++;} while(NC<NcMax);//output the calculating resultsfstream result;result.open("optimal_results.log", ios::app);if(!result){cout<<"can't open the <optimal_results.log> file!\n";exit(0);}result<<"*-------------------------------------------------------------------------*"<<endl; result<<"the initialized parameters of ACA are as follows:"<<endl;result<<"alfa="<<alfa<<", beta="<<beta<<", rou="<<rou<<", Q="<<Q<<endl;result<<"the maximum iteration number of ACA is:"<<NcMax<<endl;result<<"the shortest length of the path is:"<<BestSolution<<endl;result<<"the best route is:"<<endl;for(i=0;i<N;i++)result<<BestRoute[i]<<" ";result<<endl;result<<"*-------------------------------------------------------------------------*"<<endl<<endl; result.close();cout<<"the shortest length of the path is:"<<BestSolution<<endl;}double EvalueSolution(int *a){double dist=0;for(int i=0;i<N-1;i++)dist+=distance[a[i]][a[i+1]];dist+=distance[a[i]][a[0]];return dist;}void InCityXY( double x[], double y[], char *infile ){fstream inxyfile( infile, ios::in | ios::nocreate );if( !inxyfile ){cout<<"can't open the <"<<infile<<"> file!\n";exit(0);}int i=0;while( !inxyfile.eof() ){inxyfile>>x[i]>>y[i];if( ++i >= N ) break;}}31个城市坐标：1304 23123639 13154177 22443712 13993488 15353326 15563238 12294196 10044312 7904386 5703007 19702562 17562788 14912381 16761332 6953715 16783918 21794061 23703780 22123676 25784029 28384263 29313429 19083507 23673394 26433439 32012935 32403140 35502545 23572778 28262370 2975运行后可得到15602的巡游路径改正了n个错误。