基本蚁群算法（在VC6.0环境下实现TSP问题) OpenGL实现仿真

#include "ALGORITHM.H" #include "Common.h" //#include "MAP.H" double DB_MAX = 10e9; algorithm::algorithm() { initmap(); totalLength = 10e9; for(int i=0; i<CITY_NUM; i++) { cc[i].x = x_Ary[i]; cc[i].y = y_Ary[i]; cc[i].num = i; } for(i=0; i<CITY_NUM; i++)//计算两两城市间的距离 { for(int j=0; j<CITY_NUM; j++) { distance[i][j] = (int)(sqrt(pow((cc[i].x-cc[j].x),2)+pow((cc[i].y-cc[j].y),2)))+0.5; } } } void algorithm::updateTour() { int m = 0; int n = 0; for(int i=0;i<ANT_NUM; i++) //计算每只蚂蚁在两两城市间留下的信息素，路径越短信息素值越大 { for(int j=0; j<CITY_NUM-1; j++)//两两城市间的信息素 { m = ants[i].numberOfVisitedCity[j]; n = ants[i].numberOfVisitedCity[j+1]; temp_info[m][n] += totalInfo/ants[i].cityLength; temp_info[n][m] += totalInfo/ants[i].cityLength; } m = ants[i].numberOfVisitedCity[CITY_NUM-1]; n = ants[i].numberOfVisitedCity[0]; temp_info[m][n] += totalInfo/ants[i].cityLength; temp_info[n][m] += totalInfo/ants[i].cityLength; } //最新的环境信息素 = 消失掉的信息素 + 新留下的信息素 for(i=0; i<CITY_NUM; i++) { for(int j=0; j<CITY_NUM; j++); { envir_info[i][j] = (speedOfGone*envir_info[i][j] + temp_info[i][j]); temp_info[i][j] = 0; } } } void algorithm::initmap() { for(int i=0; i<CITY_NUM; i++) { for(int j=0; j<CITY_NUM; j++) { envir_info[i][j] = 1; temp_info[i][j] = 0; } } } void algorithm::initialAnt() { srand((unsigned)time(NULL)); int city = 0; for(int i=0; i<ANT_NUM; i++) { city = (int)(rando(CITY_NUM)+0.5); // city = rando(CITY_NUM); ants[i].addVisitedCity(city); } } void algorithm::startSearch() { int runtime = 0; double temp = 0.0; int temptour[CITY_NUM]; double dbMin = 0.0; while (runtime < SEARCH_NUM) { dbMin =100000000.0; for(int j=0; j<ANT_NUM; j++) { for(int i=0; i<CITY_NUM; i++) { ants[j].moveAnt(); } } for(j=0; j<ANT_NUM; j++) { ants[j].moveToEnd(); ants[j].updateResult();//走完更新信息素 } temp = ants[0].cityLength; for(int t=0; t<CITY_NUM; t++) { temptour[t] = ants[0].numberOfVisitedCity[t]; } for(j=0; j<ANT_NUM; j++) { if(temp >ants[j].cityLength) { temp = ants[j].cityLength; for(int t=0; t<CITY_NUM; t++) { temptour[t] = ants[j].numberOfVisitedCity[t]; } } if(dbMin >ants[j].cityLength) { DB_MAX = temp; for(int t=0; t<CITY_NUM; t++) { bestTour[t] = temptour[t]; } } if(dbMin >ants[j].cityLength) { dbMin = ants[j].cityLength; } } if(temp < totalLength) { totalLength = temp; for(int t=0; t<CITY_NUM; t++) { bestTour[t] = temptour[t]; } } printf("运行次数%d : 当前总路程：%f\n",runtime+1,totalLength); updateTour(); for(j = 0; j<ANT_NUM; j++) { ants[j].clearInfo(); } runtime++; } printf("\n最短的旅行路径是:%f",totalLength); printf("\n最优遍历路径为:"); for(int t=0; t<CITY_NUM-1; t++) { printf("%d->",bestTour[t]); } printf("%d\n",bestTour[CITY_NUM-1]); }