遗传算法C语言源代码一元函数和二元函数.docx
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遗传算法C语言源代码一元函数和二元函数.docx
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遗传算法C语言源代码一元函数和二元函数
C语言遗传算法代码
以下为遗传算法的源代码,计算一元代函数的代码和二元函数的代码以+++++++++++++++++++++++++++++++++++++为分割线分割开来,请自行选择适合的代码,使用时请略看完代码的注释,在需要更改的地方更改为自己需要的代码。
+++++++++++++++++++++++++++++++一元函数代码++++++++++++++++++++++++++++
#include
#include
#include
#include
#definePOPSIZE1000
#definemaximization1
#defineminimization2
#definecmax100
#definecmin0
#definelength120
#definechromlengthlength1//染色体长度
//注意,你是求最大值还是求最小值
intfunctionmode=minimization;
//变量的上下限的修改开始
floatmin_x1=-2;//变量的下界
floatmax_x1=-1;//变量的上界
//变量的上下限的修改结束
intpopsize;//种群大小
intmaxgeneration;//最大世代数
doublepc;//交叉率
doublepm;//变异率
structindividual
{
charchrom[chromlength+1];
doublevalue;
doublefitness;//适应度
};
intgeneration;//世代数
intbest_index;
intworst_index;
structindividualbestindividual;//最佳个体
structindividualworstindividual;//最差个体
structindividualcurrentbest;
structindividualpopulation[POPSIZE];
//函数声明
voidgenerateinitialpopulation();
voidgeneratenextpopulation();
voidevaluatepopulation();
longdecodechromosome(char*,int,int);
voidcalculateobjectvalue();
voidcalculatefitnessvalue();
voidfindbestandworstindividual();
voidperformevolution();
voidselectoperator();
voidcrossoveroperator();
voidmutationoperator();
voidinput();
voidoutputtextreport();
voidgenerateinitialpopulation()//种群初始化
{
inti,j;
for(i=0;i { for(j=0;j { population[i].chrom[j]=(rand()%20<10)? '0': '1'; } population[i].chrom[chromlength]='\0'; } } voidgeneratenextpopulation()//生成下一代 { selectoperator(); crossoveroperator(); mutationoperator(); } voidevaluatepopulation()//评价个体,求最佳个体 { calculateobjectvalue(); calculatefitnessvalue(); findbestandworstindividual(); } longdecodechromosome(char*string,intpoint,intlength)//给染色体解码 { inti; longdecimal=0; char*pointer; for(i=0,pointer=string+point;i if(*pointer-'0') {decimal+=(long)pow(2,i); } return(decimal); } voidcalculateobjectvalue()//计算函数值 { inti; longtemp1,temp2; doublex1; for(i=0;i { temp1=decodechromosome(population[i].chrom,0,length1); x1=(max_x1-min_x1)*temp1/(1024*1024-1)+min_x1; //目标函数修改开始 population[i].value=(pow(x1,5)-3*x1-1)*(pow(x1,5)-3*x1-1); //目标函数修改结束 } } voidcalculatefitnessvalue()//计算适应度 { inti; doubletemp; for(i=0;i { if(functionmode==maximization) {if((population[i].value+cmin)>0.0) {temp=cmin+population[i].value;} else {temp=0.0; } } elseif(functionmode==minimization) { if(population[i].value {temp=cmax-population[i].value;} else{temp=0.0;} } population[i].fitness=temp; } } voidfindbestandworstindividual()//求最佳个体和最差个体 { inti; doublesum=0.0; bestindividual=population[0]; worstindividual=population[0]; for(i=1;i if(population[i].fitness>bestindividual.fitness){ bestindividual=population[i]; best_index=i; } elseif(population[i].fitness { worstindividual=population[i]; worst_index=i; } sum+=population[i].fitness; } if(generation==0){ currentbest=bestindividual; } else{ if(bestindividual.fitness>=currentbest.fitness){ currentbest=bestindividual; } } } voidperformevolution()//演示评价结果 { if(bestindividual.fitness>currentbest.fitness){ currentbest=population[best_index]; } else{ population[worst_index]=currentbest; } } voidselectoperator()//比例选择算法 { inti,index; doublep,sum=0.0; doublecfitness[POPSIZE]; structindividualnewpopulation[POPSIZE]; for(i=0;i {sum+=population[i].fitness;} for(i=0;i cfitness[i]=population[i].fitness/sum; } for(i=1;i cfitness[i]=cfitness[i-1]+cfitness[i]; } for(i=0;i { p=rand()%1000/1000.0; index=0; while(p>cfitness[index]) { index++; } newpopulation[i]=population[index]; } for(i=0;i population[i]=newpopulation[i]; } } voidcrossoveroperator()//交叉算法 { inti,j; intindex[POPSIZE]; intpoint,temp; doublep; charch; for(i=0;i index[i]=i; } for(i=0;i point=rand()%(popsize-i); temp=index[i]; index[i]=index[point+i]; index[point+i]=temp; } for(i=0;i p=rand()%1000/1000.0; if(p point=rand()%(chromlength-1)+1; for(j=point;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; } } } } voidmutationoperator()//变异操作 { inti,j; doublep; for(i=0;i for(j=0;j p=rand()%1000/1000.0; if(p population[i].chrom[j]=(population[i].chrom[j]=='0')? '1': '0'; } } } } voidinput()//数据输入 {//printf("初始化全局变量: \n"); //printf("种群大小(50-500): "); //scanf("%d",&popsize); popsize=500; 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); maxgeneration=200; //printf("交叉率(0.2-0.99): "); //scanf("%f",&pc); pc=0.95; //printf("变异率(0.001-0.1): "); //scanf("%f",&pm); pm=0.03; } voidoutputtextreport()//数据输出 { inti; doublesum; doubleaverage; sum=0.0; for(i=0;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当前世代最优函数值=%f\n",generation,average,population[best_index].value); } voidmain()//主函数 {inti; longtemp1,temp2; doublex1,x2; generation=0; input(); generateinitialpopulation(); evaluatepopulation(); while(generation { 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 { printf("%c",currentbest.chrom[i]); } printf("\n"); temp1=decodechromosome(currentbest.chrom,0,length1); x1=(max_x1-min_x1)*temp1/(1024*1024-1)+min_x1; printf("x1=%lf\n",x1); //这是需要修改的地方 printf("最优值等于: %f\n",(pow(x1,5)-3*x1-1)*(pow(x1,5)-3*x1-1)); } +++++++++++++++++++++++++二元函数代码+++++++++++++++++++++++++++++++++++++++++ #include #include #include #include #definePOPSIZE500 #definemaximization1 #defineminimization2 #definecmax100 #definecmin0 #definelength120 #definelength220 #definechromlengthlength1+length2//染色体长度 //-----------求最大还是最小值 intfunctionmode=maximization; //----------- //-----------变量上下界 floatmin_x1=0; floatmax_x1=3; floatmin_x2=1; floatmax_x2=5; //----------- intpopsize;//种群大小 intmaxgeneration;//最大世代数 doublepc;//交叉率 doublepm;//变异率 structindividual { charchrom[chromlength+1]; doublevalue; doublefitness;//适应度 }; intgeneration;//世代数 intbest_index; intworst_index; structindividualbestindividual;//最佳个体 structindividualworstindividual;//最差个体 structindividualcurrentbest; structindividualpopulation[POPSIZE]; //函数声明 voidgenerateinitialpopulation(); voidgeneratenextpopulation(); voidevaluatepopulation(); longdecodechromosome(char*,int,int); voidcalculateobjectvalue(); voidcalculatefitnessvalue(); voidfindbestandworstindividual(); voidperformevolution(); voidselectoperator(); voidcrossoveroperator(); voidmutationoperator(); voidinput(); voidoutputtextreport(); voidgenerateinitialpopulation()//种群初始化 { inti,j; for(i=0;i { for(j=0;j { population[i].chrom[j]=(rand()%40<20)? '0': '1'; } population[i].chrom[chromlength]='\0'; } } voidgeneratenextpopulation()//生成下一代 { selectoperator(); crossoveroperator(); mutationoperator(); } voidevaluatepopulation()//评价个体,求最佳个体 { calculateobjectvalue(); calculatefitnessvalue(); findbestandworstindividual(); } longdecodechromosome(char*string,intpoint,intlength)//给染色体解码 { inti; longdecimal=0; char*pointer; for(i=0,pointer=string+point;i if(*pointer-'0') {decimal+=(long)pow(2,i); } return(decimal); } voidcalculateobjectvalue()//计算函数值 { inti; longtemp1,temp2; doublex1,x2; for(i=0;i { temp1=decodechromosome(population[i].chrom,0,length1); temp2=decodechromosome(population[i].chrom,length1,length2); x1=(max_x1-min_x1)*temp1/(1024*1024-1)+min_x1; x2=(max_x2-min_x2)*temp2/(1024*1024-1)+min_x2; //-----------函数 population[i].value=x1*x1+sin(x1*x2)-x2*x2; //----------- } } voidcalculatefitnessvalue()//计算适应度 { inti; doubletemp; for(i=0;i { if(functionmode==maximization) {if((population[i].value+cmin)>0.0) {temp=cmin+population[i].value;} else {temp=0.0; } } elseif(functionmode==minimization) { if(population[i].value {temp=cmax-population[i].value;} else{temp=0.0;} } population[i].fitness=temp; } } voidfindbestandworstindividual()//求最佳个体和最差个体 { inti; doublesum=0.0; bestindividual=population[0]; worstindividual=population[0]; for(i=1;i if(population[i].fitness>bestindividual.fitness){ bestindividual=population[i]; best_index=i; } elseif(population[i].fitness { worstindividual=population[i]; worst_index=i; } sum+=population[i].fitness; } if(generation==0){ currentbest=bestindividual; } else{ if(bestindividual.fitness>=currentbest.fitness){ currentbest=bestindividual; } } } voidperformevolution()//演示评价结果 { if(bestindividual.fitness>currentbest.fitness){ currentbest=population[best_index]; } else{ population[wor
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