自适应遗传算法 源代码

// SimpleGA.cpp: implementation of the CSimpleGA class. // ////////////////////////////////////////////////////////////////////// #include "SimpleGA.h" #include "ProjectHead.h" ////////////////////////////////////////////////////////////////////// // Construction/Destruction ////////////////////////////////////////////////////////////////////// CSimpleGA::CSimpleGA() { m_lMutationTimes=0; m_lMatingTimes=0; m_dSumFitness=0.0;m_dMaxFitness=0.0;m_iMaxLocation=0; m_count=0; m_nowp=0; m_position=0; last_maxfitness=0.0; } /********************************************************/ /* MATING POOL INITIAL */ /* 交配池初始化函数 */ /*********************************************************/ void CSimpleGA::Initial(int pop_size,double mutation_p,double crossing_p) { int i; m_iPopuSize=pop_size; m_dMutationP=mutation_p;m_dCrossingP=crossing_p; m_lpParents=(CGAUnite *)malloc(sizeof(CGAUnite)*m_iPopuSize); if(m_lpParents==NULL) { cout<<"内存空间分配失败！"<<endl; exit(0); } m_lpFilials=(CGAUnite *)malloc(sizeof(CGAUnite)*m_iPopuSize); if(m_lpFilials==NULL) { cout<<"内存空间分配失败！"<<endl; free(m_lpParents); exit(0); } for(i=0;i<m_iPopuSize;i++) { m_lpParents[i].Initial(); m_lpParents[i].FitnessFunction(); m_lpFilials[i]=m_lpParents[i]; } return; } /********************************************************/ /* STATISTIC FUNCTION */ /* 交配池统计函数 */ /*********************************************************/ CSimpleGA::Statistic() { int i,max_l; double sum1,max_f; sum1=0.0;max_f=0.0;max_l=0; for(i=0;i<m_iPopuSize;i++) { sum1=sum1+m_lpParents[i].m_dFitness; if(m_lpParents[i].m_dFitness>max_f) { max_f=m_lpParents[i].m_dFitness; max_l=i; } } m_dSumFitness=sum1;m_dMaxFitness=max_f;m_iMaxLocation=max_l; m_dAverageFitness=sum1/(double)m_iPopuSize; return 1; } /********************************************************/ /* SELECTION FUNCTION */ /* 个体选择函数 */ /*********************************************************/ int CSimpleGA::Selection() { double rand1,partsum; int j; partsum=0.0;j=0; rand1=(double)rand()/(double)RAND_MAX; rand1=rand1*fabs(m_dSumFitness); while((partsum<rand1)&&(j<m_iPopuSize)) { partsum=partsum+fabs(m_lpParents[j].m_dFitness);j++;} return(j); } /////////////////////////////////////////////////////// // FLIP FUNCTION // // FLIP 实验函数 // /////////////////////////////////////////////////////// int CSimpleGA::Flip(double probability) { double probability_f; // srand((unsigned)time(NULL)); probability_f=(double)rand()/(double)(RAND_MAX); if ( probability_f<=probability) return(1); else return(0); } /////////////////////////////////////////////////////// // MUTATION FUNCTION // // 变异函数 // /////////////////////////////////////////////////////// int CSimpleGA::Mutation(unsigned int loca) { int mutate; mutate=Flip(m_dMutationP); if(mutate==1) { m_lMutationTimes=m_lMutationTimes+1; if(loca==1) loca=0; else loca=1; } if(loca==1) return(1); else return(0); } /////////////////////////////////////////////////////// // MATING FUNCTION // // 杂交函数 // /////////////////////////////////////////////////////// int CSimpleGA::Mating(unsigned int *parent1_chain1,unsigned int *parent1_chain2, unsigned int *parent2_chain1,unsigned int *parent2_chain2, int k5) { int j; if(Flip(m_dCrossingP)==1) { m_lMatingTimes=m_lMatingTimes+1; for(j=0;j<GEN_LENGTH;j++) { m_lpFilials[k5].m_uGenChainA[j]=Mutation(parent1_chain1[j]); m_lpFilials[k5].m_uGenChainB[j]=Mutation(parent2_chain2[j]); m_lpFilials[k5+1].m_uGenChainA[j]=Mutation(parent2_chain1[j]); m_lpFilials[k5+1].m_uGenChainB[j]=Mutation(parent1_chain2[j]); } } else { for(j=0;j<GEN_LENGTH;j++) { m_lpFilials[k5].m_uGenChainA[j]=Mutation(parent1_chain1[j]); m_lpFilials[k5].m_uGenChainA[j]=Mutation(parent1_chain2[j]); m_lpFilials[k5+1].m_uGenChainA[j]=Mutation(parent2_chain1[j]); m_lpFilials[k5+1].m_uGenChainA[j]=Mutation(parent2_chain2[j]); } } return(1); } /********************************************************/ /* GENERATION FUNCTION */ /* 子代产生函数 */ /*********************************************************/ void CSimpleGA::Generation(void) { unsigned int mate1,mate2; int j; j=0; while(j<m_iPopuSize) { mate1=Selection(); mate2=Selection(); Mating(m_lpParents[mate1].m_uGenChainA, m_lpParents[mate1].m_uGenChainB, m_lpParents[mate2].m_uGenChainA, m_lpParents[mate2].m_uGenChainB,j); m_lpFilials[j].FitnessFunction(); m_lpFilials[j+1].FitnessFunction(); j=j+2; } return; } /********************************************************/ /* NEXT GENERATION */ /* 下一代子代产生的准备函数：父代、子代一致函数 */ /*********************************************************/ void CSimpleGA::NextGeneration() { int i; for(i=0;i<m_iPopuSize;i++) m_lpParents[i]=m_lpFilials[i]; return; } void CSimpleGA::ReportGeneration(void) { int i; //cout<<endl; m_position++; if(m_dMaxFitness>last_maxfitness) { m_count=0; m_nowp=m_position; last_maxfitness=m_dMaxFitness; } else m_count++; cout<< "现在稳定在："; cout<< m_nowp; cout<<endl; // cout<<"gen chain1: "; // for(i=GEN_LENGTH-1;i>=0;i--) // cout<<m_lpParents[m_iMaxLocation].m_uGenChainA[i]; // cout<<endl; // cout<<"gen chain2: "; // for(i=GEN_LENGTH-1;i>=0;i--) // cout<<m_lpParents[m_iMaxLocation].m_uGenChainB[i]; // cout<<endl; // cout<<"decode chain: "; // for(i=GEN_LENGTH-1;i>=0;i--) // cout<<m_lpParents[m_iMaxLocation].m_uDecodeChain[i]; // cout<<endl; // // cout<<"Parameters Are:"<<endl; // for(i=N_PARAMETER-1;i>=0;i--) // cout<<"x["<<i<<"]="<<m_lpParents[m_iMaxLocation].m_dDecValue[i]<<endl; // cout<<"Max Population Location Is: "<<m_iMaxLocation<<endl; // cout<<"Max Fitness="<<m_lpParents[m_iMaxLocation].m_dFitness<<endl; cout<<"Max Fitness="<<m_dMaxFitness<<endl; // cout<<"Average Fitness= "<<m_dAverageFitness<<endl; // cout<<"Population MutationTimes Is: "<<m_lMutationTimes<<endl; // cout<<"Population MatingTimes Is: "<<m_lMatingTimes<<endl; // cout<<"Population Affinity Is: "<<m_dAffinity<<endl; // cout<<"m_dCrossingP="<<m_dCrossingP<<"; "<<"m_dMutationP="<<m_dMutationP<<endl; return; } void CSimpleGA::FreeSpace() { free(m_lpParents); free(m_lpFilials); return; } CSimpleGA::~CSimpleGA() { } void CSimpleGA::CalcuAffinity() { double sum1,sum2; int i,j,k; sum2=0.0; for(i=0;i<m_iPopuSize;i++) { sum1=0.0; for(j=0;j<m_iPopuSize;j++) { if(i!=j) { for(k=0;k<GEN_LENGTH;k++) { if(m_lpParents[i].m_uDecodeChain[k]!=m_lpParents[j].m_uDecodeChain[k]) sum1=sum1+1.0; } } } sum2=sum2+sum1/(double)GEN_LENGTH/(double)m_iPopuSize; } m_dAffinity=sum2/(double)m_iPopuSize; return; } int CSimpleGA::SaveDate(LPCTSTR filename,char if_rewrite) { FILE *fp; if(if_rewrite=='r') fp=fopen(filename,"w+b"); else { fp=fopen(filename,"r+b"); if(fp==NULL) fp=fopen(filename,"w+"); } if(fp==NULL) return -1; fseek(fp,0,SEEK_END); fwrite(&m_dMaxFitne