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代码如下

import java.util.*; public class Tsp {       private String cityName[]={"北京","上海","天津","重庆","哈尔滨","长春","沈阳","呼和浩特","石家庄","太原","济南","郑州","西安","兰州","银川","西宁","乌鲁木齐","合肥","南京","杭州","长沙","南昌","武汉","成都","贵州","福建","台北","广州","海口","南宁","昆明","拉萨","香港","澳门"};     //private String cityEnd[]=new String[34];     private int cityNum=cityName.length;     //城市个数     private int popSize = 50;               //种群数量     private int maxgens = 20000;            //迭代次数     private double pxover = 0.8;            //交叉概率     private double pmultation = 0.05;       //变异概率     private long[][] distance = new long[cityNum][cityNum];     private int range = 2000;               //用于判断何时停止的数组区间     private class genotype {         int city[] = new int[cityNum];      //单个基因的城市序列         long fitness;                      //该基因的适应度         double selectP;                        //选择概率         double exceptp;                        //期望概率         int isSelected;                        //是否被选择     }     private genotype[] citys = new genotype[popSize];     /**      *    构造函数，初始化种群      */     public Tsp() {         for (int i = 0; i < popSize; i++) {             citys[i] = new genotype();             int[] num = new int[cityNum];             for (int j = 0; j < cityNum; j++)                 num[j] = j;             int temp = cityNum;             for (int j = 0; j < cityNum; j++) {                 int r = (int) (Math.random() * temp);                 citys[i].city[j] = num[r];                 num[r] = num[temp - 1];                 temp--;             }             citys[i].fitness = 0;             citys[i].selectP = 0;             citys[i].exceptp = 0;             citys[i].isSelected = 0;         }         initDistance();     }     /**      *  计算每个种群每个基因个体的适应度，选择概率，期望概率，和是否被选择。      */     public void CalAll(){         for( int i = 0; i< popSize; i++){             citys[i].fitness = 0;             citys[i].selectP = 0;             citys[i].exceptp = 0;             citys[i].isSelected = 0;         }         CalFitness();         CalSelectP();         CalExceptP();         CalIsSelected();     }     /**      *    填充，将多选的填充到未选的个体当中      */     public void pad(){         int best = 0;         int bad = 0;         while(true){                        while(citys[best].isSelected <= 1 && best<popSize-1)                 best ++;             while(citys[bad].isSelected != 0 && bad<popSize-1)                 bad ++;             for(int i = 0; i< cityNum; i++)                 citys[bad].city[i] = citys[best].city[i];                 citys[best].isSelected --;                 citys[bad].isSelected ++;                 bad ++;                if(best == popSize ||bad == popSize)                 break;         }     }     /**      *    交叉主体函数      */     public void crossover() {         int x;         int y;         int pop = (int)(popSize* pxover /2);         while(pop>0){             x = (int)(Math.random()*popSize);             y = (int)(Math.random()*popSize);             executeCrossover(x,y);//x y 两个体执行交叉             pop--;         }     }     /**      * 执行交叉函数      * @param 个体x      * @param 个体y      * 对个体x和个体y执行佳点集的交叉，从而产生下一代城市序列      */     private void executeCrossover(int x,int y){         int dimension = 0;         for( int i = 0 ;i < cityNum; i++)             if(citys[x].city[i] != citys[y].city[i]){                 dimension ++;             }           int diffItem = 0;         double[] diff = new double[dimension];         for( int i = 0 ;i < cityNum; i++){             if(citys[x].city[i] != citys[y].city[i]){                 diff[diffItem] = citys[x].city[i];                 citys[x].city[i] = -1;                 citys[y].city[i] = -1;                 diffItem ++;             }           }         Arrays.sort(diff);         double[] temp = new double[dimension];         temp = gp(x, dimension);         for( int k = 0; k< dimension;k++)             for( int j = 0; j< dimension; j++)                 if(temp[j] == k){                     double item = temp[k];                     temp[k] = temp[j];                     temp[j] = item;                     item = diff[k];                     diff[k] = diff[j];                     diff[j] = item;                   }         int tempDimension = dimension;         int tempi = 0;         while(tempDimension> 0 ){             if(citys[x].city[tempi] == -1){                 citys[x].city[tempi] = (int)diff[dimension - tempDimension];                 tempDimension --;             }               tempi ++;         }         Arrays.sort(diff);         temp = gp(y, dimension);         for( int k = 0; k< dimension;k++)             for( int j = 0; j< dimension; j++)                 if(temp[j] == k){                     double item = temp[k];                     temp[k] = temp[j];                     temp[j] = item;                     item = diff[k];                     diff[k] = diff[j];                     diff[j] = item;                   }         tempDimension = dimension;         tempi = 0;         while(tempDimension> 0 ){             if(citys[y].city[tempi] == -1){                 citys[y].city[tempi] = (int)diff[dimension - tempDimension];                 tempDimension --;             }               tempi ++;         }     }     /**      * @param individual 个体      * @param dimension    维数      * @return 佳点集   (用于交叉函数的交叉点）    在executeCrossover()函数中使用      */     private double[] gp(int individual, int dimension){         double[] temp = new double[dimension];         double[] temp1 = new double[dimension];         int p = 2 * dimension + 3;         while(!isSushu(p))             p++;         for( int i = 0; i< dimension; i++){             temp[i] = 2*Math.cos(2*Math.PI*(i+1)/p) * (individual+1);             temp[i] = temp[i] - (int)temp[i];             if( temp [i]< 0)                 temp[i] = 1+temp[i];         }         for( int i = 0; i< dimension; i++)             temp1[i] = temp[i];         Arrays.sort(temp1);         //排序         for( int i = 0; i< dimension; i++)             for( int j = 0; j< dimension; j++)                 if(temp[j]==temp1[i])                     temp[j] = i;          return temp;     }     /**      *    变异      */     public void mutate(){         double random;         int temp;         int temp1;         int temp2;         for( int i = 0 ; i< popSize; i++){             random = Math.random();             if(random<=pmultation){                 temp1 = (int)(Math.random() * (cityNum));                 temp2 = (int)(Math.random() * (cityNum));                 temp = citys[i].city[temp1];                 citys[i].city[temp1] = citys[i].city[temp2];                 citys[i].city[temp2] = temp;             }         }           }     /**      * 打印当前代数的所有城市序列，以及其相关的参数      */     public void print(){     /**      * 初始化各城市之间的距离      */     private void initDistance(){         for (int i = 0; i < cityNum; i++) {             for (int j = 0; j < cityNum; j++){                 distance[i][j] = Math.abs(i-j);             }         }     }     /**      * 计算所有城市序列的适应度      */     private void CalFitness() {         for (int i = 0; i < popSize; i++) {             for (int j = 0; j < cityNum - 1; j++)                 citys[i].fitness += distance[citys[i].city[j]][citys[i].city[j + 1]];             citys[i].fitness += distance[citys[i].city[0]][citys[i].city[cityNum - 1]];         }     }     /**      * 计算选择概率      */     private void CalSelectP(){         long sum = 0;         for( int i = 0; i< popSize; i++)             sum += citys[i].fitness;         for( int i = 0; i< popSize; i++)             citys[i].selectP = (double)citys[i].fitness/sum;     }     /**      * 计算期望概率      */     private void CalExceptP(){         for( int i = 0; i< popSize; i++)             citys[i].exceptp = (double)citys[i].selectP * popSize;     }     /**      * 计算该城市序列是否较优，较优则被选择，进入下一代      */     private void CalIsSelected(){         int needSelecte = popSize;         for( int i = 0; i< popSize; i++)             if( citys[i].exceptp<1){                 citys[i].isSelected++;                 needSelecte --;             }         double[] temp = new double[popSize];         for (int i = 0; i < popSize; i++) { //          temp[i] = citys[i].exceptp - (int) citys[i].exceptp; //          temp[i] *= 10;             temp[i] = citys[i].exceptp*10;         }         int j = 0;         while (needSelecte != 0) {             for (int i = 0; i < popSize; i++) {                 if ((int) temp[i] == j) {                     citys[i].isSelected++;                     needSelecte--;                     if (needSelecte == 0)                         break;                 }             }             j++;         }     }     /**      * @param x      * @return 判断一个数是否是素数的函数      */     private boolean isSushu( int x){            if(x<2) return false;            for(int i=2;i<=x/2;i++)            if(x%i==0&&x!=2) return false;            return true;         }     /**      * @param x 数组      * @return x数组的值是否全部相等，相等则表示x.length代的最优结果相同，则算法结束      */     private boolean isSame(long[] x){         for( int i = 0; i< x.length -1; i++)             if(x[i] !=x[i+1])                 return false;         return true;     }     /**      * 打印任意代最优的路径序列      */     private void printBestRoute(){         CalAll();         long temp = citys[0].fitness;         int index = 0;         for (int i = 1; i < popSize; i++) {             if(citys[i].fitness<temp){                 temp = citys[i].fitness;                 index = i;             }         }         System.out.println();         System.out.println("最佳路径的序列：");         for (int j = 0; j < cityNum; j++)         {             String cityEnd[]={cityName[citys[index].city[j]]};             for(int m=0;m<cityEnd.length;m++)             {                 System.out.print(cityEnd[m] + " ");             }         }             //System.out.print(citys[index].city[j] + cityName[citys[index].city[j]] + "  ");             //System.out.print(cityName[citys[index].city[j]]);         System.out.println();     }     /**      * 算法执行      */     public void run(){         long[] result = new long[range];         //result初始化为所有的数字都不相等         for( int i  = 0; i< range; i++)             result[i] = i;         int index = 0;       //数组中的位置         int num = 1;     //第num代         while(maxgens>0){             System.out.println("-----------------  第  "+num+" 代  -------------------------");             CalAll();             print();             pad();             crossover();             mutate();             maxgens --;             long temp = citys[0].fitness;             for ( int i = 1; i< popSize; i++)                 if(citys[i].fitness<temp){                     temp = citys[i].fitness;                 }             System.out.println("最优的解："+temp);             result[index] = temp;             if(isSame(result))                 break;             index++;             if(index==range)                 index = 0;             num++;         }         printBestRoute();     }     /**      * @param a 开始时间      * @param b   结束时间      */     public void CalTime(Calendar a,Calendar b){         long x = b.getTimeInMillis() - a.getTimeInMillis();         long y = x/1000;         x = x - 1000*y;         System.out.println("算法执行时间："+y+"."+x+" 秒");     }     /**      *    程序入口       */     public static void main(String[] args) {         Calendar a = Calendar.getInstance(); //开始时间         Tsp tsp = new Tsp();         tsp.run();         Calendar b = Calendar.getInstance(); //结束时间         tsp.CalTime(a, b);     } } 。

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