基于人工免疫优化算法

#include <stdio.h> #include<stdlib.h> #include<time.h> #include<math.h> #define LENGTH1 10 #define LENGTH2 10 #define CHROMLENGTH LENGTH1+LENGTH2 #define POPSIZE 300 int MaxGeneration =200; struct individual { char chrom[CHROMLENGTH+1]; double value;//适应度 double affective;//亲和力 double concentration;//浓度 double activity;//激励度 }; int generation; int best_index; struct individual population[POPSIZE]; struct individual nextpopulation[POPSIZE]; struct individual array[POPSIZE]; struct individual A; struct individual B; struct individual bestindividual; struct individual currentbest; int PopSize =80;//全局变量 double umu =0.08;//全局变量 double r =0.001;//全局变量 double rad =0.3; int clone_total =0;//全局变量 //***************************************************************************** void GenerateInitialPopulation(); long DecodeChromosome(char *string,int point,int length); void CalculateObjectValue(struct individual array[],int n); void Calculateaffective(struct individual array[],int n); void EvaluatePopulation(); void affectivesort(struct individual array[],int n); void clonenum(); void MutationOperator(void); void GenerateNextPopulation(void); double CalculateSimilarity(struct individual A,struct individual B); void Inhibition(void); void chongzu(); void CalculateConcentrationValue(struct individual population[],int n); void CalculateActivityValue(struct individual population[],int n); void activeslect(); void sortnewmember(); void PerformEvolution(); void FindBestIndividual(); void OutputTextReport(); //****************************************************************************** void main() { generation=0; GenerateInitialPopulation(); EvaluatePopulation(); while(generation<MaxGeneration) { generation++; GenerateNextPopulation(); EvaluatePopulation(); PerformEvolution(); OutputTextReport(); } } //*********************************************************************************** void GenerateInitialPopulation() { 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(void) { affectivesort(population,PopSize);//排序选择亲和力高的进行克隆 clonenum(); MutationOperator(); Inhibition(); chongzu(); activeslect(); sortnewmember(); } //******************************************************************************** void EvaluatePopulation(void) { CalculateObjectValue ( population,PopSize); Calculateaffective ( population,PopSize); FindBestIndividual(); } //******************************************************************************** long DecodeChromosome(char *string,int point,int length) { int i; long decimal=0L; char *pointer; for(i=0,pointer=string+point;i<length;i++,pointer++) { decimal+=(*pointer-'0')<<(length-1-i); } return(decimal); } //******************************************************************************** void CalculateObjectValue(struct individual array[],int n) { int i; long temp1,temp2; double x1,x2; for (i=0;i<n;i++) { temp1=DecodeChromosome(array[i].chrom,0,LENGTH1); temp2=DecodeChromosome(array[i].chrom,LENGTH1,LENGTH2); x1=4.096*temp1/1023.0-2.048; x2=4.096*temp2/1023.0-2.048; array[i].value=100*(x1*x1-x2)*(x1*x1-x2)+(1-x1)*(1-x1); } } //********************************************************************************** void Calculateaffective(struct individual array[],int n) { int i; for(i=0;i<n;i++) { array[i].affective=1.0/(exp(-(r*array[i].value))+1.0); } } //********************************************************************************** void affectivesort(struct individual array[],int n) { int i,j; struct individual a; for(j=0;j<n-1;j++) { for(i=0;i<n-1-j;i++) { if(array[i].affective<array[i+1].affective) { a=array[i+1]; array[i+1]=array[i]; array[i]=a; } } } } //****************************************************************** void FindBestIndividual() { int i; bestindividual=population[0]; for(i=0;i<PopSize;i++) { if(population[i].affective>bestindividual.affective) { bestindividual=population[i]; best_index=i; } if(generation==0) { currentbest=bestindividual; } else { if(bestindividual.affective>currentbest.affective) { currentbest=bestindividual; } } } } void PerformEvolution() { if(bestindividual.affective>currentbest.affective) { currentbest=population[best_index]; } } //********************************************************************************** void clonenum() { int i,j; int M =100; int m[POPSIZE]; int L=0; double sum1=0; double sg =0.8; for(i=0;i<(int)(sg*M);i++) { sum1+=array[i].affective; m[i]=(int)(array[i].affective*M/sum1); clone_total+=m[i]; } for(i=0;i<(int)(sg*M);i++) { for(j=0;j<m[i];j++) nextpopulation[L++]=array[i]; } } //******************************************************************************** void MutationOperator(void) { int i,j; double p,po; for(i=0;i<clone_total;i++) { for(j=0;j<CHROMLENGTH;j++) { po=rand()%1000/1000.0; p=exp((-1)*nextpopulation[i].affective); if(po<p) { nextpopulation[i].chrom[j]=(nextpopulation[i].chrom[j]=='0')?'1':'0'; } } } } //******************************************************************************** double CalculateSimilarity (struct individual A,struct individual B) { int j=0; double sum=0.0; for(j=0;j<CHROMLENGTH;j++) { sum+=(A.chrom[j]=B.chrom[j])?0:1; } sum=sum*(log(2.0))/CHROMLENGTH; return sum; } //************************************************************************************************ void Inhibition(void) { int i,j; int L=0; int numinh=0; //double rad =0.3; CalculateObjectValue(nextpopulation,clone_total); Calculateaffective(nextpopulation,clone_total); affectivesort(nextpopulation,clone_total);//排序进行抑制 for(i=0;i<clone_total-1;i++) { for(j=i+1;j<clone_total;j++) { if(CalculateSimilarity(nextpopulation[i],nextpopulation[j])>rad) { nextpopulation[++L]=nextpopulation[j]; } } clone_total=L+1; L=i+1; } clone_total=L+1; } //***************************************************************************************************** void chongzu() { int i; for(i=0;i<clone_total;i++) { population[i+PopSize]=nextpopulation[i]; } affectivesort(population,clone_total+PopSize);//很重要，去掉200代找不到最优解。 } //******************************************************************************************************* void CalculateConcentrationValue(struct individual population[],int n) { int i,j,m=0; for(i=0;i<n;i++) { for(j=0;j<n;j++) { m+=(CalculateSimilarity(population[i],population[j])<rad)?1:0; } } population[i].concentration=m*(1.0)/(n); } //*********************************************************************************************************** void CalculateActivityValue(struct individual population[],int n) { int i; double h=1.5; for(i=0;i<n;i++) { population[i].activity=population[i].affective*exp(-population[i].concentration/h); } } //************************************************************************************************************* void activeslect(