yichuansuanfa.rar_极大值_极小值

#include "iostream.h" #include "math.h" #include "stdlib.h" #include "iomanip.h" #include "time.h" //-------------------------参数区------------------------------------------ const int popsize=40; //种群规模 const int N=2; //维数 const int generation=200; //进化代数 const int number=100; const double pc=0.3; //交叉概率 const double pm=0.1; //变异概率 //const int num=0; //-------------------------函数声明区------------------------------------------ void Initialize(double p1[][N],double x1[N],double x2[N]); //初始化种群 void CalObjValue(double p1[][N],double *p2); double CalObjvalueIndi(double p1[][N],int i); void CalFitvalueMax(double *p1,double *p2); //计算适应度值,p1->objvalue,p2->fitvalue void BestReplace(double & CurrentBestFitValue,double *p1,double p2[][N], double *p3); void TournamentSelection(double p1[][N],double *p2,double p3[][N]);// 联赛选择算法 void ArithmeticCossover(double p1[][N]);//算数交叉 void GaussianMutation(double p[][N],double x1[N],double x2[N]);//高斯变异 void Climbing(double p1[][2],double x1[N],double x2[N]); //下坡法 //-------------------------子函数区------------------------------------------ void Initialize(double p1[][N],double x1[N],double x2[N]) //初始化种群 { for(int i=0;i<popsize;i++) //p1指向POP { for(int j=0;j<N;j++) { double temp=x2[j]+(x1[j]-x2[j])*(double)rand()/(double)32767; p1[i][j]=temp; } } } void CalObjValue(double p1[][N],double *p2) { for(int i=0;i<popsize;i++) { double temp; temp=CalObjvalueIndi(p1,i); p2[i]=temp; } } void CalFitvalueMax(double *p1,double *p2) //计算适应度值,p1->objvalue,p2->fitvalue { for(int i=0;i<popsize;i++) { double cmin=100; p2[i]=p1[i]+cmin; } } void BestReplace(double & CurrentBestFitValue,double *p1,double p2[][N], double *p3) //p1->fitvalue,p2->pop,p3->currentbestindividual { for(int i=0;i<popsize;i++) { if(p1[i]>CurrentBestFitValue) { CurrentBestFitValue=p1[i]; for(int j=0;j<N;j++) p3[j]=p2[i][j]; } } } void TournamentSelection(double p1[][N],double *p2,double p3[][N])// 联赛选择算法 //p1->pop,p2->fitvalue,p3->newpop { for(int i=0;i<popsize;i++) { int point1=floor((popsize-1)*rand()/(double)32767+0.5); int point2=floor((popsize-1)*rand()/(double)32767+0.5); if(p2[point1]>p2[point2]) { for(int j=0;j<N;j++) { p3[i][j]=p1[point1][j]; } } else { for(int j=0;j<N;j++) { p3[i][j]=p1[point2][j]; } } } } void ArithmeticCossover(double p1[][N])//算数交叉 //p1->newpop { for(int i=0;i<popsize-1;i+=2) for(int j=0;j<N;j++) { double rands=(double)rand()/(double)32767; double alpha=(double)rand()/(double)32767; if(rands<pm) { double temp1=p1[i][j]; double temp2=p1[i+1][j]; p1[i][j]=alpha*temp2+(1-alpha)*temp1; p1[i+1][j]=alpha*temp1+(1-alpha)*temp2; } } } void GaussianMutation(double p[][N],double x1[N],double x2[N])//高斯变异 { int i,j; double temp; int m; double rand_vector[12]; double sum; for(i=0;i<popsize;i++) { for(j=0;j<N;j++) { double s=(double)rand()/(double)32767;//产生一个随机数s if(s<pc) //如果产生的随机数小于交叉概率 { temp=x2[j]-1; //temp没有实际意义，只是为了使得while循环得以启动 while(temp<x2[j]||temp>x1[j]) { for(m=0;m<12;m++) { rand_vector[m]=(double)rand()/(double)32767; }//产生随机数组 sum=0; for(m=0;m<12;m++) { sum=sum+rand_vector[m]; }//计算12个随机数的和 temp=p[i][j]+(x1[j]-x2[j])/6*(sum-6); //(x1max-x1min)/6为方差，可根据实际情况任意选取 } p[i][j]=temp; } } } } void Climbing(double p1[][N],double x1[N],double x2[N]) //下坡法 { double TempPop[popsize][N]; double rand_vector[12]; double sum; double temp; double step; double old_objvalue; double old_fitvalue; double new_objvalue; double new_fitvalue;//定义新旧适应度值 double delta_fitvalue=0; for(int x=0;x<popsize;x++) for(int y=0;y<N;y++) TempPop[x][y]=p1[x][y];//将Nbestpop赋给temp_Nbestpop; for(int i=0;i<popsize;i++) { for(int j=0;j<N;j++) { //-----------对某个体的某维进行高斯变异------------------------------------ temp=x2[j]-1;//使得while循环能够启动 while(temp<x2[j]||temp>x1[j]) { for(int m=0;m<12;m++) { rand_vector[m]=(double)rand()/(double)32767; }//产生随机数组 sum=0; for(m=0;m<12;m++) { sum=sum+rand_vector[m]; }//计算12个随机数的和 temp=p1[i][j]+(sum-6)*(x1[j]-x1[j])/6; //(sum-6)*(x1max-x1min)/6为方差，可调整 TempPop[i][j]=temp; } old_objvalue=CalObjvalueIndi(p1,i); //objvalue和fitvalue综合在一起了 old_fitvalue=old_objvalue+100; new_objvalue=CalObjvalueIndi(TempPop,i); //objvalue和fitvalue综合在一起了 new_fitvalue=new_objvalue+100; delta_fitvalue=old_fitvalue-new_fitvalue; if(delta_fitvalue<0) //新的适应度数值大 { step=TempPop[i][j]-p1[i][j]; while(delta_fitvalue<0) { p1[i][j]=TempPop[i][j]; //将新的数值付给POP TempPop[i][j]+=step; old_objvalue=CalObjvalueIndi(p1,i); //objvalue和fitvalue综合在一起了 old_fitvalue=old_objvalue+100; new_objvalue=CalObjvalueIndi(TempPop,i); //objvalue和fitvalue综合在一起了 new_fitvalue=new_objvalue+100; delta_fitvalue=old_fitvalue-new_fitvalue; } } } } } //-------------------------主函数区------------------------------------------ void main() { int num=0; double RelativeErrorx=0; double RelativeErrory=0; srand(time(NULL)); //初始化时间种子 for(int k=0;k<number;k++) { double pop[popsize][N]; //浮点数种群 double newpop[popsize][N]; double objvalue[popsize]; //目标函数值 double fitvalue[popsize]; //适应度值 double CurrentBestIndividual[N]={0}; //当前最优个体 double CurrentBestFitValue=0; //当前最优适应度值,初始值设为0 double Xmax[N]={2.048,2.048}; double Xmin[N]={-2.048,-2.048}; //srand(time(NULL)); //初始化时间种子 //for(int k=0;k<number;k++) //{ Initialize(pop,Xmax,Xmin); //初始化种群 for(int t=0;t<generation;t++) { CalObjValue(pop,objvalue); CalFitvalueMax(objvalue,fitvalue); //计算适应度值,p1->objvalue,p2->fitvalue BestReplace(CurrentBestFitValue,fitvalue,pop,CurrentBestIndividual); TournamentSelection(pop,fitvalue,newpop);// 联赛选择算法 ArithmeticCossover(newpop);//算数交叉 GaussianMutation(newpop,Xmax,Xmin);//高斯变异 Climbing(newpop,Xmax,Xmin); CalObjValue(newpop,objvalue); //CalFitvalueMax(objvalue,fitvalue); //计算适应度值 //BestReplace(CurrentBestFitValue,fitvalue,newpop,CurrentBestIndividual); for(int i=0;i<popsize;i++) for(int j=0;j<N;j++) pop[i][j]=newpop[i][j]; } cout<<"当前最优目标函数值："<<endl; cout<<CurrentBestFitValue-100<<endl; RelativeErrorx=CurrentBestIndividual[0]*100; RelativeErrory=CurrentBestIndividual[1]*100; cout<<"最优个体所在位置："<<endl; cout<<"x="<<CurrentBestIndividual[0]<<endl<<"y="<<CurrentBestIndividual[1]<<endl; cout<<endl<<endl; //RelativeErrorx=(abs(CurrentBestIndividual[0])-0.0898)/0.0898*100;