yichuansuanfa.rar_遗传算法 极值

#include <stdio.h> #include<stdlib.h> #include<time.h> #include<math.h> #define POPSIZE 500 #define maximization 1 #define minimization 2 #define cmax 100 #define cmin 0 #define length1 10 #define length2 10 #define chromlength length1+length2 //染色体长度 int functionmode=maximization; int popsize; //种群大小 int maxgeneration; //最大世代数 double pc; //交叉率 double pm; //变异率 struct individual { char chrom[chromlength+1]; double value; double fitness; //适应度 }; int generation; //世代数 int best_index; int worst_index; struct individual bestindividual; //最佳个体 struct individual worstindividual; //最差个体 struct individual currentbest; struct individual population[POPSIZE]; //函数声明 void generateinitialpopulation(); void generatenextpopulation(); void evaluatepopulation(); long decodechromosome(char *,int,int); void calculateobjectvalue(); void calculatefitnessvalue(); void findbestandworstindividual(); void performevolution(); void selectoperator(); void crossoveroperator(); void mutationoperator(); void input(); void outputtextreport(); void generateinitialpopulation( ) //种群初始化 { int i,j; for (i=0;i<popsize; i++) { for(j=0;j<chromlength;j++) { population[i].chrom[j]=(rand()%10<5)?'0':'1'; } population[i].chrom[chromlength]='\0'; } } void generatenextpopulation() //生成下一代 { selectoperator(); crossoveroperator(); mutationoperator(); } void evaluatepopulation() //评价个体，求最佳个体 { calculateobjectvalue(); calculatefitnessvalue(); findbestandworstindividual(); } long decodechromosome(char *string ,int point,int length) //给染色体解码 { int i; long decimal=0; char*pointer; for(i=0,pointer=string+point;i<length;i++,pointer++) if(*pointer-'0') {decimal +=(long)pow(2,i); } return (decimal); } void calculateobjectvalue() //计算函数值 { int i; long temp1,temp2; double x1,x2; for (i=0; i<popsize; i++) { temp1=decodechromosome(population[i].chrom,0,length1); temp2=decodechromosome(population[i].chrom,length1,length2); x1=4.096*temp1/1023.0-2.048; x2=4.096*temp2/1023.0-2.048; population[i].value=100*(x1*x1-x2)* (x1*x1-x2)+(1-x1)*(1-x1); } } void calculatefitnessvalue()//计算适应度 { int i; double temp; for(i=0;i<popsize;i++) { if(functionmode==maximization) {if((population[i].value+cmin)>0.0) {temp=cmin+population[i].value;} else {temp=0.0; } } else if (functionmode==minimization) { if(population[i].value<cmax) {temp=cmax-population[i].value;} else{ temp=0.0;} } population[i].fitness=temp; } } void findbestandworstindividual( ) //求最佳个体和最差个体 { int i; double sum=0.0; bestindividual=population[0]; worstindividual=population[0]; for (i=1;i<popsize; i++){ if (population[i].fitness>bestindividual.fitness){ bestindividual=population[i]; best_index=i; } else if (population[i].fitness<worstindividual.fitness) { worstindividual=population[i]; worst_index=i; } sum+=population[i].fitness; } if (generation==0){ currentbest=bestindividual; } else{ if(bestindividual.fitness>=currentbest.fitness){ currentbest=bestindividual; } } } void performevolution() //演示评价结果 { if (bestindividual.fitness>currentbest.fitness){ currentbest=population[best_index]; } else{ population[worst_index]=currentbest; } } void selectoperator() //比例选择算法 { int i,index; double p,sum=0.0; double cfitness[POPSIZE]; struct individual newpopulation[POPSIZE]; for(i=0;i<popsize;i++) {sum+=population[i].fitness;} for(i=0;i<popsize; i++){ cfitness[i]=population[i].fitness/sum; } for(i=1;i<popsize; i++){ cfitness[i]=cfitness[i-1]+cfitness[i]; } for (i=0;i<popsize;i++) { p=rand()%1000/1000.0; index=0; while (p>cfitness[index]) { index++; } newpopulation[i]=population[index]; } for(i=0;i<popsize; i++){ population[i]=newpopulation[i]; } } void crossoveroperator() //交叉算法 { int i,j; int index[POPSIZE]; int point,temp; double p; char ch; for (i=0;i<popsize;i++){ index[i]=i; } for (i=0;i<popsize;i++){ point=rand()%(popsize-i); temp=index[i]; index[i]=index[point+i]; index[point+i]=temp; } for (i=0;i<popsize-1;i+=2){ p=rand()%1000/1000.0; if (p<pc){ point=rand()%(chromlength-1)+1; for (j=point; j<chromlength;j++){ ch=population[index[i]].chrom[j]; population[index[i]].chrom[j]=population[index[i+1]].chrom[j]; population[index[i+1]].chrom[j]=ch; } } } } void mutationoperator() //变异操作 { int i,j; double p; for (i=0;i<popsize;i++){ for(j=0;j<chromlength;j++){ p=rand()%1000/1000.0; if (p<pm){ population[i].chrom[j]=(population[i].chrom[j]=='0')?'1':'0'; } } } } void input() //数据输入 { printf("初始化全局变量:\n"); printf(" 种群大小(50-500)："); scanf("%d", &popsize); if((popsize%2) != 0) { printf( " 种群大小已设置为偶数\n"); popsize++;}; printf(" 最大世代数(100-300)："); scanf("%d", &maxgeneration); printf(" 交叉率(0.2-0.99)："); scanf("%f", &pc); printf(" 变异率(0.001-0.1)："); scanf("%f", &pm); } void outputtextreport()//数据输出 { int i; double sum; double average; sum=0.0; for(i=0;i<popsize;i++) {sum+=population[i].value;} average=sum/popsize; printf("当前世代=%d\n当前世代平均函数值=%f\n当前世代最高函数值=%f\n",generation,average,population[best_index].value); } void main() //主函数 { int i; printf("本程序为求函数y=100*(x1*x1-x2)*(x1*x2-x2)+(1-x1)*(1-x1)的最大值 \n其中-2.048<=x1,x2<=2.048\n"); generation=0; input(); generateinitialpopulation(); evaluatepopulation(); while(generation<maxgeneration) { generation++; generatenextpopulation(); evaluatepopulation(); performevolution(); outputtextreport(); } printf("\n"); printf(" 统计结果: "); printf("\n"); printf("最大函数值等于：%f\n",currentbest.fitness); printf("其染色体编码为："); for (i=0;i<chromlength;i++) { printf("%c",currentbest.chrom[i]); } printf("\n"); }