基于案例学习的粒子群算法 Matlab实现

#include "iostream.h" #include "stdlib.h" #include "stdio.h" #include "math.h" #include "time.h" #define POPSIZE 100 #define DIMENSION 30 //********************************************88 #define POP_SIZE 40 //粒子规模 #define MAX_GEN 5000 //最大迭代次数 #define DIMEN 30 //维数 #define X_MAX 5.12 //正向最大边界 //*************************************************** int popsize; //粒子群规模 int maxgeneration; //最大迭代次数 int generation; //迭代次数 int dimension; //维数 int a; int Tu[POPSIZE]; //没有更新最优解的代数 double w; double c1; double c2; double vmax; double vmin; double xmax; double xmin; double maxf; double maxf1; double minf; double f[POPSIZE]; double f1[POPSIZE]; double x[POPSIZE][DIMENSION]; double v[POPSIZE][DIMENSION]; double pbest[POPSIZE][DIMENSION]; double gbest[DIMENSION]; double BandOne[20][DIMENSION]; double BandOneFitness[20]; int BandOneSize=0; void generateinitialpopulation(); void generatenextpopulation(); void calculateobjectvalue(); void calculatenewobjectvalue(); void findgbestandmaxf(); void findgworstandminf(); void renewgbestandmaxf(); void rennewgworstandminf(); void input(); void outputreport(); void outputinitialpopulation(); void V_update(int i); void MinSDFirst(int i); //初始化粒子群 void generateinitialpopulation() { int i,j; double r1,r2; for(i=0;i<popsize;i++) { for(j=0;j<dimension;j++) { r1=(double)rand()/RAND_MAX; x[i][j]=(xmax-xmin)*r1+xmin; r2=(double)rand()/RAND_MAX; v[i][j]=(vmax-vmin)*r2+vmin; pbest[i][j]=x[i][j]; } } } //计算适值 void calculateobjectvalue() { int i,j,k; double ff=1,f0[200]; for(i=0;i<popsize;i++) { f[i]=0; //ff=1; //F11: Generalized Girewank Function //f0[i]=0; //F10:Ackley's Function //f[i]=fabs(x[i][0]); //f4:Schwefel's Problem 2.21 for(j=0;j<dimension;j++) //F5时 dimension-1 { //f[i]=f[i]+x[i][j]*x[i][j]; //F11: Generalized Girewank Function //ff=ff*cos(x[i][j]/sqrt(j+1)); //F11: Generalized Girewank Function //f[i]=f[i]+x[i][j]*x[i][j]; //F10:Ackley's Function //f0[i]=f0[i]+cos(2*3.14156*x[i][j]); //F10:Ackley's Function f[i]=f[i]+x[i][j]*x[i][j]-10*cos(2*3.14156*x[i][j])+10;//F9:Generalized Rastrigin //f[i]=f[i]-x[i][j]*sin(sqrt(fabs(x[i][j]))); //F8:Generalzed Schwefel's problem //f[i]=f[i]+(j+1)*pow(x[i][j],4); //f7:Quartic Function //f[i]=f[i]+int(x[i][j]+0.5) * int(x[i][j]+0.5);//f6:Step Function //f[i]=f[i]+100*(x[i][j+1]-x[i][j]*x[i][j])*(x[i][j+1]-x[i][j]*x[i][j])+(x[i][j]-1)*(x[i][j]-1); //f5:Generalized Rosenbrock //if(f[i]<fabs(x[i][j])) //f4:Schwefel's Problem 2.21 // f[i]=fabs(x[i][j]); //f4:Schwefel's Problem 2.21 //ff=0; //f3:Schwefel's Problem 1.2 //for(k=0;k<=j;k++) //f3:Schwefel's Problem 1.2 // ff=ff+x[i][k]; //f3:Schwefel's Problem 1.2 //f[i]=f[i]+ff*ff; //f3:Schwefel's Problem 1.2 //ff=ff*fabs(x[i][j]); //f2:Schwefel's Problem 2.22 //f[i]=f[i]+fabs(x[i][j]); //f2:Schwefel's Problem 2.22 //f[i]=f[i]+x[i][j]*x[i][j]; //f1:Sphere Model } //f0[i]=exp(f0[i]/30); //F10:Ackley's Function //f[i]=-20*exp(-0.2*sqrt(f[i]/30))-f0[i]+20+exp(1); //F10:Ackley's Function //f[i]=f[i]+(double)(1.0*rand()/RAND_MAX); //f7:Quartic Function //f[i]=f[i]+ff; //f2:Schwefel's Problem 2.22 //f[i]=f[i]/4000-ff+1;//F11: Generalized Girewank Function } } //计算适值 void calculatenewobjectvalue() { int i,j,k; double ff=1,f0[200]; for(i=0;i<popsize;i++) { f1[i]=0; //ff=1; //F11: Generalized Girewank Function //f0[i]=0; //F10:Ackley's Function //f1[i]=fabs(x[i][0]); //f4:Schwefel's Problem 2.21 for(j=0;j<dimension;j++) //F5时 dimension-1 { //f1[i]=f1[i]+x[i][j]*x[i][j]; //F11: Generalized Girewank Function //ff=ff*cos(x[i][j]/sqrt(j+1)); //F11: Generalized Girewank Function //f1[i]=f1[i]+x[i][j]*x[i][j]; //F10:Ackley's Function //f0[i]=f0[i]+cos(2*3.14156*x[i][j]); //F10:Ackley's Function f1[i]=f1[i]+x[i][j]*x[i][j]-10*cos(2*3.14156*x[i][j])+10;//F9:Generalized Rastrigin //f1[i]=f1[i]-x[i][j]*sin(sqrt(fabs(x[i][j]))); //F8:Generalzed Schwefel's problem //f1[i]=f1[i]+(j+1)*pow(x[i][j],4); //f7:Quartic Function //f1[i]=f1[i]+int(x[i][j]+0.5) * int(x[i][j]+0.5);//f6:Step Function //f1[i]=f1[i]+100*(x[i][j+1]-x[i][j]*x[i][j])*(x[i][j+1]-x[i][j]*x[i][j])+(x[i][j]-1)*(x[i][j]-1);//f5:Generalized Rosenbrock //if(f1[i]<fabs(x[i][j])) //f4:Schwefel's Problem 2.21 // f1[i]=fabs(x[i][j]); //f4:Schwefel's Problem 2.21 //ff=0; //f3:Schwefel's Problem 1.2 //for(k=0;k<=j;k++) //f3:Schwefel's Problem 1.2 // ff=ff+x[i][k]; //f3:Schwefel's Problem 1.2 //f1[i]=f1[i]+ff*ff; //f3:Schwefel's Problem 1.2 //ff=ff*fabs(x[i][j]); //f2:Schwefel's Problem 2.22 //f1[i]=f1[i]+fabs(x[i][j]); //f2:Schwefel's Problem 2.22 //f1[i]=f1[i]+x[i][j]*x[i][j]; //f1:Sphere Model } //f0[i]=exp(f0[i]/30); //F10:Ackley's Function //f1[i]=-20*exp(-0.2*sqrt(f1[i]/30))-f0[i]+20+exp(1); //F10:Ackley's Function //f1[i]=f1[i]+(double)(1.0*rand()/RAND_MAX); //f7:Quartic Function //f1[i]=f1[i]+ff; //f2:Schwefel's Problem 2.22 //f1[i]=f1[i]/4000-ff+1;//F11: Generalized Girewank Function } } //找出适值最大的解 void findgbestandmaxf() { int i,j; for(j=0;j<dimension;j++) gbest[j]=x[0][j]; calculateobjectvalue(); maxf=f[0]; for(i=0;i<popsize;i++) { if(maxf>f[i]) { maxf=f[i]; for(j=0;j<dimension;j++) gbest[j]=x[i][j]; } } } //更新适值最大的解 void renewgbestandmaxf() { int i,j,maxn; double temp; for(i=0;i<popsize;i++) { if(f1[i]<f[i]) { f[i]=f1[i]; Tu[i]=0; for(j=0;j<dimension;j++) pbest[i][j]=x[i][j]; } else Tu[i]++; } maxf1=f1[0]; maxn=0; for(i=0;i<popsize;i++) { if(maxf1>f1[i]) { maxf1=f1[i]; //记下本代找到的最优解值 maxn=i; //记下对应的粒子下标 } } //**********************[榜样策略]*************************************************************** //temp=0; //for(j=0;j<dimension;j++) // temp+=fabs(x[maxn][j]-gbest[j]); //for(i=0;i<BandOneSize;i++) // for(j=0;j<dimension;j++) // temp+=fabs(x[maxn][j]-BandOne[i][j]); //temp=temp/dimension; if(BandOneSize<popsize*0.1) //如果BandOne集合没有满，则增加一个BandOne成员 { BandOneFitness[BandOneSize]=maxf1; for(j=0;j<dimension;j++) BandOne[BandOneSize][j]=x[maxn][j]; BandOneSize++; } else //如果BandOne集合满了，则替换一个资历最老且比当前最优差的成员 { for(i=0;i<BandOneSize;i++) if(BandOneFitness[i]>maxf1) { for(j=0;j<dimension;j++)