人工鱼群算法的java运行代码

package AFAS; //import java.util.Random; import java.util.Date; public class myAFAS { public myAFAS() { // TODO 自动生成的构造函数存根 } int fish_number; // 人工鱼群的规模 int try_number; // 尝试次数 int dim; // 人工鱼状态空间维数 double step; // 人工鱼移动的步长 double delta; // 拥挤度因子 double[][] distance; // 人工鱼的距离 double visual; // 视野 fish[] g_f; // 人工鱼群 fish best_fish; // 鱼群中的最有人工鱼个体 fish f_next[]; // 人工鱼的下一步 int index; // 当前最优值的人工鱼索引值 double DELTA[]; double XH[]; double init_X[][]; //初始化人工鱼状态 public myAFAS( int n,int ws, double v, int t, double step, double dt ) { fish_number = n; try_number = t; this.step = step; delta = dt; dim = ws; visual = v; g_f = new fish[fish_number]; // 生成人工鱼群 } // 初始化函数 public void init(int fish_num,int dim, double visual, int t, double s, double d) { fish_number = fish_num; try_number = t; step = s; delta = d; this.dim = dim; this.visual = visual; g_f = new fish[fish_number]; // 生成人工鱼群 int i=0,j=0; init_X = new double[fish_number][dim]; // 对整个鱼群进行初始化 for( i=0; i<fish_number; ++i ) { g_f[i] = new fish(); g_f[i].init(dim, visual); for(j=0; j<dim; ++j) init_X[i][j] = g_f[i].X[j]; System.out.println("fit:"+g_f[i].fit); } double distance[][] = new double[fish_number][fish_number]; // 计算距离 for( i=0; i<fish_number; ++i ) for( j=i; j<fish_number; ++j ) { if(i!=j ) { distance[i][j] = calDistance(g_f[i].X, g_f[j].X, dim); distance[j][i] = distance[i][j]; } else { distance[i][j]=0.00001; } } // DELTA = new double[dim]; XH = new double[dim]; // 对其他人工鱼的初始化 best_fish = new fish(); best_fish.init(dim,visual); // 初始化最有人工鱼 best_fish.fit = -999999; // 此时 ， 最有人工鱼的最优值为-0xffffffff(无穷小) //原来是f_n，我改成了f_next //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! f_next = new fish[3]; f_next[0] = new fish(); f_next[1] = new fish(); f_next[2] = new fish(); //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! f_next[0].init(dim,visual); f_next[1].init(dim,visual); f_next[2].init(dim,visual); // cout<<best_fish.fit<<endl; } // 计算两个人工鱼之间的距离 public double calDistance( double x1[], double x2[], int size ) { // ofstream cout("pos.txt", ios::app); double dis=0.0; for( int i=0; i<size; ++i ) { // System.out.print(x1[i]+" "+x2[i]); dis += (x1[i]-x2[i])*(x1[i]-x2[i]); } if(Math.abs(dis)<0.0001 ) { dis=0.0001; } // System.out.print("dis:"+dis+" 开方："+Math.sqrt(dis)); return Math.sqrt(dis); // 返回结果 } //混沌 public void hunDun(int ind) { int i=0; param.Z = param.U2*( param.Z*(1-param.Z) ); for( i=0; i<dim; i++ ) { DELTA[i] = -visual+2*visual*param.Z; DELTA[i] = visual -param.U1*DELTA[i]*DELTA[i]; //原来是f_n，我改成了f_next XH[i] = f_next[0].X[i]+DELTA[i]; } double temp = f_next[0].consistence(XH, dim ); if( temp > f_next[0].fit ) { for( i=0; i<dim; i++ ) { f_next[0].X[i] = XH[i]; } param.hd++; // System.out.print("hd="+param.hd); f_next[0].fit = temp; } } // 混沌 public void hunDun_new(int ind ) { int i=0; for( i=0; i<dim; ++i ) { DELTA[i] = -visual+2*visual*init_X[ind][i]; //原来是f_n，我改成了f_next XH[i] = f_next[ind].X[i]+DELTA[i]; } double temp = f_next[ind].consistence(XH, dim ); if( temp > f_next[ind].fit ) { // System.out.print(""flag"); for( i=0; i<dim; i++ ) { f_next[ind].X[i] = XH[i]; } param.hd++; // System.out.print("hd="+param.hd); f_next[ind].fit = temp; } } // 觅食行为 public void prey(int ind) { // ofstream cout("prey.txt", ios::app ); int i,j; /* static int tt=(unsigned)time(NULL); srand((unsigned)time(NULL)+tt++); long r1 = System.currentTimeMillis(); Random rand = new Random(r1); double r = (2*(rand.nextDouble())-1)*param.Umax; */ // double r = (2*(Math.random())-1)*param.Umax; fish new_fish = new fish(); new_fish.init(dim,visual); System.out.println("dim="+dim); for(i=0; i<try_number; ++i ) // 进行try_number次尝试 { for(j=0; j<dim; j++ ) { //new_fish.X[j] = visual*rand()/(double)RAND_MAX; new_fish.X[j] = (2*(Math.random())-1)*param.Umax; // System.out.println("new_fish.X["+j+"]:"+new_fish.X[j]); } new_fish.fit = new_fish.consistence(new_fish.X, dim); // System.out.println("new_fish.fit:"+new_fish.fit); // 如果f_n1的食物浓度大于当前人工鱼的食物浓度 if( new_fish.fit > g_f[ind].fit ) { // double dis = calDistance( new_fish.X, g_f[ind].X,dim); // 计算X_new 与X[ind]d的距离 for( j=0; j<dim; j++ ) f_next[0].X[j] = new_fish.X[j]; // g_f[ind].X[j]+(new_fish.X[j]-g_f[ind].X[j])*step*rand()/(double)RAND_MAX/dis; f_next[0].fit =f_next[0].consistence(f_next[0].X,dim); // new_fish.fit; } else { for( j=0; j<dim; j++ ) // f_next[0].X[j] = g_f[ind].X[j]+step*rand()/(double)RAND_MAX; f_next[0].X[j] = g_f[ind].X[j]+step*Math.random(); f_next[0].fit = f_next[0].consistence(f_next[0].X, dim ); } } // 加入混沌 // hunDun(ind ); } //聚群行为 public void swarm( int ind ) { int nf = 0; double X_center[] = new double[param.DIM]; // 中心位置 //memset( X_center,0,sizeof(X_center) ); int i,j; // 计算人工鱼的中心位置 for( j=0; j<fish_number; ++j ) { if( distance[ind][j]<visual ) { nf++; for( i=0; i<dim; ++i ) { X_center[i] += g_f[j].X[i]; } } } for( i=0; i<dim; i++ ) X_center[i] /=nf; // 人工鱼的中心位置 // 满足条件 double dis=0.0; // static int tt=(unsigned)time(NULL); // srand((unsigned)time(NULL)+tt++); //f_n->f_next f_next[1].fit = f_next[1].consistence( X_center, dim ); if( f_next[1].fit/nf > delta*g_f[ind].fit ) { dis = calDistance(X_center,g_f[ind].X,dim ); for( i=0; i<dim ; ++i ) f_next[1].X[i] = g_f[ind].X[i]+ // (X_center[i]-g_f[ind].X[i])*step*rand()/(double)RAND_MAX/dis; (X_center[i]-g_f[ind].X[i])*step*Math.random()/dis; } else { prey(ind); // 不满足条件执行觅食行为 } // } //追尾行为 public void follow(int ind) { int i,j; double dis = 0.0; double max = -999999; double max_x[]=new double[param.DIM]; for( j=0; j<fish_number; ++j ) { if( distance[ind][j]<visual && g_f[j].fit>max ) { max = g_f[j].fit; for( i=0; i<dim; i++ ) max_x[i] = g_f[j].X[i]; index = j; } } int nf = 0;